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SELF-EVALUATION OF COMPUTER SCIENCE DOCTORAL STUDIES PROGRAM University of Latvia Riga, 2001
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SELF-EVALUATION OFCOMPUTER SCIENCE DOCTORAL STUDIES
PROGRAM
University of LatviaRiga, 2001
Contents
Introduction................................................................................................................31 Aims and Objectives...............................................................................................32 General Characterization of the Studies Program...................................................43. The Content and Organization of the Studies Program.........................................54 Doctoral Studies and Evaluation of the Results......................................................65. Support and the Resources.....................................................................................7
5.1. The Resources.................................................................................................75.2. The Management of the Studies......................................................................75.3 The Research at the Department......................................................................7
6 The Collaboration within the Curriculum...............................................................87 The Student Evaluation Methods............................................................................88 The Comparison with Similar Curricula in Other Countries..................................89 Conclusion...............................................................................................................9
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Introduction
Computer Science (CS) academic program was designed using the expertise of the academic staff of the University of Latvia to prepare highly qualified specialists in computer science and software engineering and our being informed on the experience of several leading foreign universities in organizing doctoral studies in Computer Science and Information Technology. Computer Science Doctoral Studies program of the University of Latvia was considered and approved by the Branch (Computer Science) Doctoral Studies Council, Council of the Faculty of Physics and Mathematics, the Science Council of the University of Latvia, and the Senate of the University of Latvia (February 28, 2000, dec. No. 175).
Computer Science Doctoral Studies program consists of four subprograms: Mathematical Foundations of Computer Science, Computer and Systems Programming, Programming Languages and Systems, Data Processing Systems and Computer Networking.
This Self-evaluation is performed according to the “Law on Higher Educational Establishments”, the law “On Research Activities”, “Law on Education”, UL Constitution, UL Doctoral Studies Programme, “Regulation of the Order and Criteria of Promotion” (Regulation No. 134 of the Cabinet of Ministers, April 6, 1999) and the Regulation governing Doctoral Studies at the University of Latvia (adopted at the UL Research Council Meeting on October 6, 1999, Protocol No.1)
Computer Science Doctoral Studies program was compared with similar doctor studies programs in the University of Stockholm, Sweden, University College London, United Kingdom, University of Maryland, College Park, U.S.A., University of Helsinki, Finland, University of Bonn (Rheinische Friedrich-Wilhelms-Universität Bonn), Germany. It was found that the programs are essentially similar.
1 Aims and Objectives
The aim of the Computer Science (CS) academic program is to ensure the academic education in computer science and to prepare highly qualified specialists in computer science and software engineering for the growing needs of the information technology industry in Latvia. To achieve this goal the curriculum
provides the students with the relevant theoretical and practical knowledge in computer science and software engineering,
trains the students to apply their knowledge and to work independently and creatively while acquiring new knowledge.
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Doctoral students must carry out well documented: - - -- acquisition of practical application of the latest research methods in the Computer Science;
- acquisition of the latest methods of information technology, research planning, data processing and presentation;
- comprehensive acquisition of theoretical disciplines of Computer Science;
- acquisition of lecturing and project management skills by participation in the implementation of Bachelor and Master study programmes as well as research projects;
- participation with reports in international seminars, conferences, schools;
- in-service training in other universities completed by publication of joint results;
- independent presentation of research results and their submission for publication in journals and collections of scientific papers..
The first 3 years, i.e. 156 weeks of full-time doctoral studies are financed from the UL budget. The part-time doctoral studies may be financed by natural and legal entities. Tuition fees for doctoral studies are set by the Senate of UL.
2 General Characterization of the Studies ProgramDoctoral Thesis and Examinations
A doctoral thesis can be a monography, a dissertation, publication of which reflects the candidate’s complete original research, and the results of which are considered to be a significant contribution to the development of Computer Science.
Major results of a doctoral thesis are to be published or to be accepted for publishing in a certain number of research articles, minimum number of which and conditions for publishing are defined by the regulations of MK LR and decisions of LSC.
If a doctoral thesis is submitted a collection of publications, it has to be submitted as one banded work, which contains a summary in the Latvian language in the volume of at least 1 page written by the author (40000 signs). It has to give a possibility to judge about the unity of these publications, its methodical setting, common goals of the research, as well as its tasks and conclusions. Published works and works accepted for publishing are attached.
Any doctoral thesis has a summary that is necessary for external expert examination. It is to be written in the volume of at least one page in the English language, or any other language that corresponds with specific features of a scientific branch. If a doctoral thesis is written in any foreign language that corresponds with
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specific features of a branch a summary has to be submitted in the Latvian language and in the English language or any other language, that corresponds with specific features of a branch. A summary has to reflect innovational aspects of a work, its methodical aspects, a review on its results and conclusions, as well as a list of published and prepared works and a list of conferences, on which it was reported about the results of a doctoral thesis, have to be attached.
A committee set up by the Doctor studies council and appointed with the rector’s order takes promotional examinations.
3. The Content and Organization of the Studies Program3.1 The contents of doctoral studies.
The program is organized to provide independent research with an aim to obtain original and verified results in Computer Science.
Doctoral students must carry out well documented:- acquisition of practical application of the latest research methods in the corresponding branch;- acquisition of the latest methods of information technology, research
planning, data processing and presentation;
- comprehensive acquisition of theoretical disciplines of Computer Science;- acquisition of lecturing and project management skills by participation in the
implementation of Bachelor and Master study programmes as well as research projects;
- participation with reports in international seminars, conferences, schools;
- - in-service training in other universities completed by publication of joint results;
- - independent presentation of research results and their submission for publication in research editions.
3.2 The organization of doctoral studies
The student in contact with his thesis advisor produces the Individual Plan. The fulfillment of the Individual Plan is monitored by the Doctoral Studies Council, the Director of Doctoral Studies in Computer Science, the subprogram professor, and the thesis advisor.
The professor regularly monitors the correspondence of the real process of the studies and the Individual Plan. At the end of the academic year the professor provides the information to the Director of Doctoral Studies in Computer Science. This information and the formal report by the doctoral student is the grounds for continuation of the financing of the doctoral studies for the subsequent academic year.
The doctoral student reports once per year to the Council of Doctoral Studies in Computer Science. It is recommended to organize this report in a form of a
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scienrtific seminar. The final decision of the possibility to continue the financing of the doctoral studies is made by the Council of Doctoral Studies in Computer Science.The presence of the thesis advisor is expected.
At the end of the doctoral studies the Council of Doctoral Studies in Computer Science organizes a seminar where the final results of the doctoral studies are considered, and the decision is taken whether to recommend to send the thesis to the Promotion Council, or to advice the doctoral student how to continue the work on the thesis.
After the completion of the doctoral studies the thesis is being presented to the Promotion Council in Computer Science by the University of Latvia (headed by prof. Jānis Bārzdiņš).
4 Doctoral Studies and Evaluation of the Results
The lecture courses for the doctoral students are delivered by Doctors andHabilitated Doctors:
Prof. Jānis Bārzdiņš.
Prof. Rūsiņš Mārtiņš Freivalds.
Prof. Audris Kalniņš.
Asoc. prof. Guntis Bārzdiņš.
Asoc. prof. Jānis Bičevskis .
Asoc. prof. Juris Borzovs.
Asoc. prof. Kārlis Čerāns.
Asoc. prof. Jānis Cīrulis.
Asoc. prof. Ēvalds Ikaunieks.
Asoc. prof. Paulis Ķikusts.
Asoc. prof. Kārlis Podnieks.
Asoc. prof. Juris Strods.
Asoc. prof. Māris Treimanis.
Doc. Edvīns Karnītis.
Doc. Juris Vīksna.
Curricula Vitae of these specialists are attached as Supplement 8. The programs of the provided courses of lectures are attached as Supplement 5.
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5. Support and the Resources
5.1. The Resources
Financial resources are provided by the Faculty of Physics and Mathematics. These resources are composed from the state budget finances and the fees from part-time doctoral students. The fees at this moment are established at the level 450 Latvian lats per year which is considerably lower than the real costs.
The doctoral students can use creditation from Latvian banks. Full-time doctoral students receive a stipend.
The doctoral students can freely use the Library of the University of Latvia and the faculty library.
The high qualification of the lecturers and the theses advisors make a strong possibility for the students to have their studies successful.
5.2. The Management of the Studies
The studies are managed by the Council of Doctoral Studies in Computer Science of the University of Latvia. The Council is headed by the Director of Doctoral Studies in Computer Science of the University of Latvia.
The Council of Doctoral Studies in Computer Science of the University of Latvia establishes the regularity of the doctoral studies and supervises the studies process.
5.3 The Research at the Department
As a rule, each member of the staff is teaching a course in a specially where they are among the most qualified experts in Latvia. Most of them are participating in the research funded by the Latvian Council of Science (LCS), grants of European Union, or other major research projects. In particular:
LCS research program “The Development of Competitive Information Technology Production in Latvia”, Prof. J. Bārzdiņš, participants - K. Podnieks, A. Kalniņš, G. Bārzdiņš, P. Íikusts, K. Čerāns, M. Treimanis, J. Bičevskis, J. Borzovs, J. Strods et al.
LCS research grant 01.0354 “Quantum Automata and their Capabilities”.
LCS research grant 01.0301 “The Algorithmic Theory of Discovery and its Applications in Systems Analysis and Bioinformatics” - Prof.; J. Bārzdiņš, participants - A. Brāzma, J. Vīksna, U. Sarkans, et al.
EU ESPRIT project Nr. 23287 ADDE, the coordinator from Latvia - A. Kalniņš, participants K. Podnieks, J. Barzdins, U. Sarkans, J. Vîksna, P. Ķikusts.
Swedish Academy project ML-2000, coordinator from Latvia - Prof. R. Freivalds, participants P. Íikusts, J. Vîksna, J. Smotrovs, G. Tervits.
“The Development of Information Systems for Education in Latvia” - M. Treimanis, participants J. Bièevskis, H. Bondars, U.Straujums as well as a number of Master students
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several software development projects for the customers in Latvia and Western countries - J. Borzovs, J. Strods, etc.
The most part of the staff have publication in international scientific editions. An impressive number of international publications has been written by R. Freivalds, and also by Prof. J. Bārzdiņš and Prof. A. Kalniņš. Many of the staff are consultants in various projects (in particular M. Treimanis, J. Bièevskis and J. Borzovs).
Many students are participating in the research. For instance, A. Ambainis was graduating the curriculum with a MSS. degree having many international scientific publications. At the moment A. Ambainis is a Ph.D. student in the Berkeley University, USA.
6 The Collaboration within the CurriculumThe B.Sc. Curriculum is basically taught by the full-time staff of the Faculty of Physics and Mathematics of the University of Latvia, and is helped by the part-time staff, whose principal affiliation is mainly the Institute of Mathematics and Computer Science (IMCS).
The MSS curriculum has been implemented differently. Most subjects are taught by part-time staff, whose main affiliation is IMCS or other institutions. This allows to involve specialists of the highest qualification for teaching the respective subjects. IMCS is playing the leading role in the implementations of the MSS curriculum Physically the teaching is located within the premises of IMCS. The staff of IMCS involved in delivering the CS M.Sc curriculum are part-time members of the Faculty of Physics and Mathematics. At the same time several full-time members of the Faculty are also involved in the curriculum.
7 The Student Evaluation MethodsThe students are evaluated accordingly to the regulations of the Teaching Council and the Senate of the University of Latvia.
1. The quality indicators:
10 grade evaluation system in the obligatory subjects
yes/no system in some voluntary subjects
2. The quantity indicator - the number of credits
8 The Comparison with Similar Curricula in Other CountriesFor comparison we have used the following universities:
University of Helsinki (Computer Science)
University of Pittsburgh (USA) (Computer Science)
Stockholm University (Computer and System Sciences)
University of Maryland (USA) (Computer Science)
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The Table 1 contains detailed comparison of our Computer Science Curricula with Curricula of Helsinki university and Curricula of Pittsburgh university. In the curricula in these universities coincide in most parts with minor variations. Most of the differences are at the M.Sc course level. Different universities have different principal specializations, apparently depending on the interests and the qualification of the particular staff.
For instance at the University of Pittsburgh the emphasis (in M.Sc level) is on concurrent, distributed and real time systems, parallel algorithms, robot programming, image recognition and artificial intelligence. It should be noted that most of these subjects are not particularly important in the job market in Latvia.
The main stress of our University has been put on systems modeling and software engineering for systems like Information systems.
In general the curriculum of CS at the University of Latvia is compatible with similar curricula at the mentioned universities. It should also be noted that the textbooks that are used in teaching are typically the same as the ones used in the western universities.
9 ConclusionThe bachelors and masters curricula in computer science provide high academic qualification regarding computer science and prepare good professionals in the area of software design. The curricula are based upon the recommendations of “Curriculum’91” taking into account the contents of the respective curricula in USA and EU as well as the local characteristics of Latvian software industry. The curricula of computer science and the teaching process is organized accordingly to the Charter of the University of Latvia, the decisions of the Senate and the Study Council of the University of Latvia and other regulatory documents.
The advantages of the curricula
1. Programs are consistent with the recommendations and the respective curricula in EU and USA.
2. Professors perform scientific studies of world-wide interest and work at high-tech government projects; thus ensuring the quality of the curricula and introducing there the state-of-the-art information technologies.
3. Highly motivated students facing serious competition when applying to the computer science study programs facilitate the implementation of the curricula.
4. Modern computing equipment, communications, software and lecture halls ensure qualitative implementation of the curricula.
The disadvantages of the curricula
1. Students are demanded by the job market, many students work while they study. This leads to the increase of the average time of studies.
2. Many professors, being busy with government projects, do not have time to defend their scientific results in doctoral committees and to get their scientific degrees.
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The necessity of bachelors and masters curricula in the University of Latvia is caused by the demands of the rapidly growing information industry in Latvia.
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UNIVERSITY OF LATVIA
Program of Doctoral Studies
Computer Science(Name of program)
Doctor degree in computer science(Name of degree)
Dr.sc.comp.
Program director: Rūsiņš Mārtiņš Freivalds (name, surname)
Dr.Hab.sc.comp., Professor
AFFIRMED at a meeting of the Computer Science Doctoral Program Council on 20.08.1999.
___________ / / (signature)
AFFIRMEDat a meeting of the Council of theFaculty of Physics and Mathematics on 30.08.99.
___________ / / (signature)
AFFIRMEDat a meeting of the University of Latvia Council of Science on 27.10.1999.
___________ / /(signature)
AFFIRMEDat a meeting of the University of Latvia Senate on 29.11.1999.
___________ / /(signature)
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ABSTRACT
Computer Science (CS) academic program was designed using the expertise of the academic staff of the University of Latvia to prepare highly qualified specialists in computer science and software engineering and our being informed on the experience of several leading foreign universities in organizing doctoral studies in Computer Science and Information Technology.
Computer Science Doctoral Studies program consists of four subprograms: Mathematical Foundations of Computer Science, Computer and Systems Programming, Programming Languages and Systems, Data Processing Systems and Computer Networking.
Enrolment into the Computer Science doctoral studies program is allowed only for persons with a Master degree either in Computer Science or in mathematics, or with documents of education corresponding to these degrees.
As an exception, a person can be enrolled into the Computer Science doctoral studies program if he/she has a considerable work experience in closely related fields, and has sufficient knowledge in Computer Science and mathematics.
Admission exams take place in form of an interview. The interviews are organized by the Computer Science doctoral studies council.
Grades of the applicant at preceding levels of studies, results of the interview, papers published by the applicant, talks given by the applicant at scientific conferences, pedagogical experience, professional experience, and participation in research programs are considered in the application process.
Full-time studies take 3 years (52 weeks per year, 40 hours per week). They are funded from the state budget. Part-time studies take 4 years (36 weeks per year, 40 hours per week). They are funded by individuals and legal entities. The amount of studies (both full-time and part-time) equals 144 credits. 44 credits are to be taken for theoretical courses and practical activities. 100 credits is the amount of the promotion project.
To be admitted to the promotion procedure, the doctorant is to pass promotion exams in the speciality and foreign language, to publish at least 5 papers in respectable scientific journals and to present reports at no less than 2 international scientific conferences. The form of the thesis may be a dissertation, a monograph or (in exceptional cases) a collection of published papers.
As a result of the doctoral studies the doctorant and the defence at the Promotion Council the doctorant is expected to obtain the academic degree doctor of Computer Science (Dr. sc.comp.).
1. General Characterization of the Studies Program
1.1 The aim of the Computer Science (CS) academic program (referred below as PROGRAM) is to ensure the academic education in computer science and to prepare highly qualified specialists in computer science and software engineering for the growing needs of the information technology industry in Latvia, to provide for the participating students competence and academic degree corresponding to Ph.D. degree in Computer Science.
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1.2 As the result of the graduation from the PROGRAM and the promotion procedure in the Promotion Council the participant obtains the academic degree doctor of Computer Science (Dr. sc.comp.).
1.3 PROGRAM consists of four subprograms: Mathematical Foundations of Computer Science, Computer and Systems Programming, Programming Languages and Systems, Data Processing Systems and Computer Networking.
1.4 PROGRAM is structured into: UL Doctoral Studies program (UL Senate decision No. 50, October 26, 1998);
Computer Science doctoral studies program (approved by UL Senate); the individual programs produced by the doctorants together with their scientific
advisors in coordination with the Doctoral Studies Program of the University of Latvia (approved by LU Senate Decision No.50, October 26, 1998).
1.5. Management of PROGRAM
1.5.1. PROGRAM is produced by UL Computer Science doctoral studies council (see Appendix 6).
1.5.2. PROGRAM is approved by UL Senate.l.5.3. UL Computer Science doctoral studies council determines the organization the
doctoral studies and delegates the rights to the professors of the corresponding subbranches.
1.5.4. PROGRAM is coordinated by the Program Director. The Program Director is appointed by the UL Doctoral Studies Program Director, Research Prorector of the University of Latvia.
l.6. Implementation of doctoral studies.
1.6.1. Doctoral studies are implemented in the divisions of the Faculty of Physics and Mathematics and the Institute of Mathematics and Computer Science, University of Latvia.
1.6.2. See the list of the directions of research of the involved divisions and the Institute of Mathematics and Computer Science, University of Latvia in Appendix 2.
1.6.3. See the list of the professors, associated professors and the subbranches represented by them in Appendix 3.
l.7. Amount of the doctoral studies.
1.7.1. PROGRAM allows full-time and part-time studies.1.7.2. Full-time studies take 3 years (52 weeks per year, 40 hours per week). 48
weeks each year are working weeks and 4 weeks are vacation weeks.1.7.3. Part-time studies take 4 years (36 weeks per year, 40 hours per week).1.7.4. The overall amount of academic credits for doctoral studies is 144. This
amount is made of theoretical courses (44 credits) and work on the promotion project (100 credits).
1.8. Funding of Doctoral Studies.
1.8.1. Full-time doctoral studies are funded by subsidies from the UL budget 3 years, i.e. 156 weeks.
l.8.2. Part-time studies are funded by individuals and legal entities.
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1.8.3. Costs of Doctoral Studies are calculated by Doctoral Studies Council, and adopted by the UL Senate.
2. Enrollment and the beginning of studies
2.1. Enrollment into the Computer Science doctoral studies program is allowed only for persons with a Master degree either in Computer Science or in mathematics, or with documents of education corresponding to these degrees.
2.2. As an exception, a person can be enrolled into the Computer Science doctoral studies program if he/she has a considerable work experience in fields listed in p. 1.3, and has sufficient knowledge in Computer Science and mathematics. (Such a case is decided in an interview).
2.3. Foreign applicants are admitted provided they have appropriate education. The correspondence between the documents is established by experts of the Academic Information Center.
2.4. Applicants for doctoral studies funded from the state budget participate in the competition for the state budget funding. The competition is organized by the UL Doctoral Studies Unit.
2.5. Admission exams take place in form of an interview. The interviews are organized by the Computer Science doctoral studies council.
2.6. In the admission process the following criteria are considered:
2.6.1. Grades of the applicant at the corresponding Master’s program;2.6.2. results of the interview;2.6.3. papers published by the applicant;2.6.4. talks given by the applicant at scientific conferences;2.6.5. pedagogical experience;2.6.6. professional experience.2.6.7. participation in research programs.
2.7. The distribution of vacancies for doctoral studies funded from the state budget is adopted by UL Research Council.
2.8. Every person enrolled for doctoral studies funded from individual resources or resources of legal entities signs a special contract with the University of Latvia.
3. Content of doctoral studies
3.1. The overall amount of academic credits for doctoral studies is 144. This amount consists of:
1. Theoretical courses (corresponding to the subbranch, see below) – 24 credits.
2. Specialization course (the content is approved individually by the Computer Science doctoral studies council) – 24 credits.
3. New methods of research in Computer Science, Information Technologies and presentation of results – 2 credits.
4. Preparation for and participation in scientific conferences, workshops, seminars, schools, participation in implementation of Computer Science Bachelor and Master programs – 2 credits.
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5. Individual research and work on the promotion project – 100 credits.
3.2 Theoretical courses in subbranches
1. Subbranch Mathematical Foundations of Computer Science
- Algorithms, automata and formal languages – 4 credits- Data protection and cryptography – 2 credits- Effective algorithms, their construction and analysis – 4 credits- Specification languages – 4 credits- Artificial Intelligence – 4 credits- Computer graphics – 4 credits- Verification of programs – 2 credits
2. Subbranch Computer and System Programming
- Object-oriented programming – 4 credits- Object-oriented analysis and modeling – 4 credits- Computer networking – 8 credits- UML language and its application – 2 credits- Operating systems – 4 credits- Project management – 2 credits
3. Subbranch Programming Languages and Systems
- Object-oriented programming – 4 credits- Object-oriented analysis and modeling – 4 credits- Algorithms, automata and formal languages – 4 credits- UML language and its application – 2 credits- Project management – 2 credits- Business modeling languages and tools – 4 credits- Compilers – 4 credits
4. Subbranch Data Processing Systems and Computer Networks
- Object-oriented programming – 4 credits- Object-oriented analysis and modeling – 4 credits- Data protection and cryptography – 2 credits- Computer networking – 8 credits- UML language and its application – 2 credits- Design of information systems – 2 credits- Project management – 2 credits
Note. Computer Science doctoral studies council can give a permission to change two of abovementioned courses (no more than 8 credits).
3.3. Promotion project forms and requirements
3.3.1. A doctoral thesis reflects candidate’s complete original research, and the results of which are considered to be a significant contribution to the development of Computer Science.
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3.3.2. A doctoral thesis can be a monograph, a dissertation or (in exceptional cases) a collection of strongly related published papers.
3.3.3. Whatever the form of the thesis, a summary of it has to be submitted in the Latvian language and in the English language
3.3.4. The main results of the thesis are to be published (or accepted for publication) in at least five papers in refereed scientific journals (regular publications) included in the list of well-known regular scientific publications approved by the Latvian Scientific Council.
4. Doctoral studies and their supervision
4.1 The doctorant (in co-ordination with his/her scientific advisor and with respect to the decisions of the Computer Science doctoral studies council) produces individual program of studies for the current year.
4.2. Activities which the doctoral student carries out under the individual program, their scope and evaluation once per year are approved of with a signature by the scientific advisor, the chairman of the Computer Science doctoral studies council. They are followed by UL Doctoral Studies Unit.
4.3. The subbranch professor regularly checks the correspondence of the studies to the individual plan, and in relation to the regulations produced by UL Doctoral Studies Unit and the Computer Science doctoral studies council reports to the PROGRAM director. This report and a positive evaluation is the ground for funding the subsequent year of the studies.
4.4. At the end of the year the doctorant reports to scientific seminar of the corresponding subbranch. Protocol with the decision of the seminar is submitted to the PROGRAM director. The seminar is organized by the Computer Science doctoral studies council with a participation of specialists and members of the Promotion Council.
4.5. Final decision of the results of the yearlong studies is taken by the Computer Science doctoral studies council.
4.6. At the end of the doctoral studies the results are discussed at a seminar organized by the subbranch professor. The decision to send the thesis to the Promotion Council or to continue the work on the thesis is taken.
4.7. After the completion of the doctoral studies UL Doctoral Studies Unit (based on the records in the doctorant’s Individual Card) produces the Certificate of Graduation. The Certificate is not produced if the thesis is not sent the Promotion Council.
4.8. The program for the promotion exam in the speciality is produced by the subbranch professor and it is approved by the Computer Science doctoral studies council. The committee for the exam is organized by the Promotion Council. At least one of the members of the committee is to be a member of the Computer Science doctoral studies council. The expiration date of the validity of the exam is established by the Promotion Council.
5. Means to facilitate the doctoral studies program
5.1. Knowledge base of the research in UL.
5.1.1. Monographs and scientific journals in the libraries of the University of Latvia.
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5.1.2. Collections of papers, proceedings of conferences and workshops in the library of the faculty of Physics and Mathematics, Institute of Mathematics and Computer Science, divisions of the Faculty and the Institute.
5.2. Bachelor, Master and Professional programs in Computer Science. Participation in these programs allows the doctorants to get experience of presentation and pedagogical experience.
5.3. Grants and research projects of divisions of the Faculty and the Institute, among them being international projects.
5.4 International scientific conferences and seminars organized by the Faculty and the Institute.
5.5 Collections of papers produced by the Faculty and the Institute.5.6 The doctoral thesis can be defended at the Computer Science Promotion Council
of the University of Latvia.
5.7 Costs of Doctoral Studies are calculated by the Computer Science doctoral studies council, taking into account the ratio of the branch and program level; they are adopted by the UL Senate. Doctoral Studies fees may not be lower than the fee adopted by the UL Senate.
6. Self-evaluation of the studies program
Expenses of the Doctoral studies program consists of the stipend of the doctorant, remuneration of the scientific advisor, social tax, expenses to organize lectures and seminars, infrastructure of the doctoral studies, travel expenses, literature.
Expenses Yearly / student
1 . Stipend of the doctorant 696
2. Remuneration of the scientific advisor 150
3. Social tax 229
4. Lectures and seminars 190
5. Infrastructure of doctoral studies 305
6. Travel expenses 500
7. Literature 300
Total 2370
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Curriculumof Doctoral
studentsin Computer Science
Course Abstracts
Affirmedin the Council of Department of Physics and Mathematics
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Prof. Rūsiņš Mārtiņš FreivaldsProgram director
Riga, Raiņa boulv. 29tel.: (371) 7226997fax.: (371) 7820153e-mail: [email protected]
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CONTENTS
Mandatory courses (A) 4Construction and Analysis of Efficient AlgorithmsObject-oriented Analysis and ModelingObject-Oriented Programming and C++
Specialized elective courses (B) 11
Algorithmic Methods in Artificial IntelligenceAlgorithms, Automata and Formal Languages IAlgorithms, Automata and Formal Languages IIBusiness BasicsBusiness Modeling Languages and Tools - a CASE StudyBusiness Process ReengineeringCompilersComputer GraphicsComputer Networks IComputer Networks IIDatabase Fundamentals IDatabase Fundamentals IIData Protection and CryptographyFoundations of Specification LanguagesInformation Systems DesignMathematical Logic in Computer ScienceMetamodels and Formal SpecificationsOffice AutomationOperating SystemsOracle BasicsProgram TestingManagement Information SystemsProject ManagementProgram VerificationSoftware QualitySystem DesignUML and its Applications
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Construction and Analysis of Efficient Algorithms
Author: docent Alvis Brāzma, Dr.sc.comp.Volume: 4 credits, 64 hoursSemester: Testing form: examinationPrerequisites: essential knowledge of programming, data structures, and
mathematics Course group:
Abstract
The basic difference between highly qualified programmers and amateurs is in the skills of the first in solving nontrivial algorithmic problems. This course is aimed at providing the students with the necessary knowledge to acquire these skills. The course discusses the basic algorithmic paradigms, the principles of the analysis of algorithms, and gives examples of many simple, but nontrivial algorithms that are used in practice. This will show that many brute-force solutions of even simple algorithmic problems are highly inefficient, and will teach the student to look for alternative, more efficient solutions in many of the day-to-day programming tasks.
Content
1. The constant time initialization of arrays;
2. The function growth order notion and its applications; practical examples how to evaluate different functions;
3. The notion of the time and space complexity of the algorithms for iterative and recursive algorithms; practical examples how to evaluate the complexity of practical algorithms;
4. Search algorithms; binary and interpolation search;
5. Heap;
6. Sorting algorithms; merge-sort, heap-sort, quick-sort, digital sorting;
7. Data structures for dictionaries; dictionary operations, static and dynamic dictionaries, skip-lists, AVL-trees, 2-3-trees;
8. Hashing - the basic idea, conflict resolution methods, extendible hashing, hashing functions (division, multiplications, universal hashing);
9. Data structures for trees and graphs and tree and graph traversal, topological sorting;
10. Greedy algorithms; construction the minimal spanning tree for a graph; Huffman code;
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11. Dynamic programming; memorization techniques; the distance between two nodes in a DAG; editing distance between two strings and the searching of an approximate substring occurrence; longest common subsequence;
12. Dijkstra=92s shortest path algorithm;
13. Fast algorithms for substring search (KMP, BM, RK algorithms);
14. Compression algorithms.
Specific topics may change from year to year following the advances of the computer science and the interests of the author.
Credit requirements.
1. To pass two written tests;
2. To submit two home-works within the required deadlines;
3. At the end of the semester to be able to answer questions about the topics covered in the course (for instance, after a quick consultation of notes or a book, to be able to show on a concrete example how a particular algorithm discussed in the course works on a concrete example).
Literature
1. Harry R.Lewis and Larry Denenberg. Data Structures and their Algorithms.
2. HarperCollins Publishers, 1991
3. Robert Sedgewic. Algorithms in C. Addison-Wesley Publishing Company, 1990
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Object-oriented Analysis and Modeling
Author professor Jānis Bārzdiņš, Dr. habil. sc.comp.Volume 4 credits, 64 hoursSemesterTesting form examination with project defensePrerequisites noneCourse group
AbstractThe course treats in detail the methods and means of object-oriented modeling. The basis for that is Object Modeling Technique (OMT) by J. Rumbaugh. OMT is compared with other methods of object-oriented modeling, including Unified Modeling Language (UML). Course briefly discusses the tools supporting object-oriented modeling. Course is taught on the basis of examples which are discussed in seminar sessions.
ContentsThe goal of the course is to discuss the methods of analysis and modeling of object-oriented systems and to teach the students their practical use. 1. Introduction. What is modeling, how it differs from programming. Different kinds
of modeling. 2. The basic elements of OMT (according to J. Rumbaugh):
2.1. Objects and classes.2.2. Links and associations (relations)2.3. Attributes and operations2.4. Aggregation2.5. Generalization and inheritance2.6. An example of object model (class diagram)2.7. Discussion about a more precise semantics of the object model (class
diagram)2.8. Some advice how to build object models2.9. Problems 3.1-3.32 from the J.Rumbaugh textbook
3. More possibilities of object-oriented modeling (OMT) by J. Rumbaugh3.1. A deeper understanding of aggregation and generalization3.2. Recursive aggregates, examples3.3. Abstract classes3.4. Multiple inheritance3.5. Object model constraints3.6. Further advice for building object models3.7. Problems 4.1-4.18 from the J. Rumbaugh textbook.
4. UML as a further development of OMT4.1. Comparison of UML and OMT notation4.2. More possibilities of UML class diagrams4.3. Deeper understanding of classification and aggregation4.4. Stereotypes, their usage4.5. Interfaces and abstract classes4.6. Parametrized classes
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5. Tool “GRADE Modeler”, how to build object models5.1. Brief overview of “GRADE Modeller”5.2. More detailed exposition of “GRADE Modeller” with respect to its class
diagram building possibilities6. Discussion of real examples
6.1. A system of automated teller machines (ATM)6.2. Building object models for real systems which students encounter in their
practical life7. Conceptual modeling
7.1. Language and reality7.2. Basic concepts of conceptual modeling7.3. Examples of conceptual models7.4. Comparing conceptual and object modeling
8. “Use case” diagrams and their usage8.1. The elements and their semantics in “Use case” diagrams8.2. The usage of “Use case” diagrams
9. Brief overview of the stuff beyond object modeling – dynamics modeling, modeling of data flow, object-oriented programming
Credit Requirements During the course students should be able to use the methods of object-oriented analysis and modeling and to use some tool supporting these methods. To pass the exam a student should:1. Give a presentation during the seminar about some course topic2. Complete an examination project – build an object model for a given real system
and to defend the project.
Literature1. J. Rumbaugh et al. Object-oriented modeling and design. Prentice Hall, 1991. 2. M. Fowler. UML distilled. Addison-Wesley, 1997.3. Unified Modeling Language. See: www.rational.com/uml.4. G. Booch, J. Rumbaugh and I. Jacobson. Unified Modeling Language User Guide.
Addison-Wesley, 1997. 5. J. Rumbaugh, I. Jacobson and G. Booch. Unified Modeling Language Reference
Manual. Addison Wesley, 1997. 6. J. A.Bubenko, P.Johannesson and MBowman. Conceptual Modeling, Prentice
Hall, 1997. 7. GRADE Version 4.0. How to start modeling. User Guide.8. GRADE Version 4.0. Object Modeling: CL diagrams. User Guide.
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Object-Oriented Programming and C++
Author docent Guntis Barzdins, Dr.sc.comp., Uģis Sarkans, Mag.sc.comp.Volume 4 credits, 64 hoursSemester Testing form examinationPrerequisites noneCourse group
AbstractIn the introductory part of the course motivation, main principles and features of object-oriented programming are discussed. The main part of the course is devoted to mastering programming language C++, explaining every language construct first with simpler examples and proceeding to more advanced questions. In parallel some issues of the theory of object-oriented programming are covered. In the conclusion the main principles and methodology of object-oriented development are discussed.
Contents
I. Motivation of object-oriented programming.
A. Software quality indicators.
B. Modular software development.
C. Reusability.
D. Levels of object-orientation.
II. Abstract data types.
III. Basic constructs of C++ language.
A. Variable declarations and definitions.
B. Types of variables.
C. Library function usage.
D. Relation operators.
E. Branching.
F. Loops.
IV. Complex types in C++ language.
A. Structures.
B. Enumerated types.
V. Functions.
A. Declarations, definitions, call.
B. Parameter passing and return mechanisms.
C. Function overloading.
VI. Classes.
A. Class specification.
B. Class usage.
C. Constructors and destructors.
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D. Static class members.
VII. C++ arrays.
A. Definition, initialization, usage.
B. Multidimensional arrays.
C. Strings.
VIII. Pointers in C++.
A. Pointer variables.
B. Connection between arrays and pointers.
C. Parameter passing with pointers.
D. Dynamic memory – operators new and delete.
IX. C++ streams.
A. Motivation of streams.
B. Hierarchy of stream support libraries.
C. Files and streams.
X. Operator overloading.
A. Unary operators.
B. Binary operators.
C. Data type conversion.
XI. C++ inheritance mechanism.
A. Base class and derived class.
B. Abstract base class.
C. Multilevel inheritance.
XII. Virtual functions.
A. Comparison with non-virtual functions.
B. Late binding.
C. Friend functions.
XIII. Support of assignment and copy operations.
XIV. Templates.
A. Function templates.
B. Class templates.
XV. Exception handling.
XVI. Theoretical questions.
A. Responsibilities and contracts in object-oriented programming.
B. Canonical class definition.
C. Parametrized types.
XVII. Design and development.
A. Aim and means of design.
B. Design cycle.
C. Design steps.
D. Class hierarchy construction.
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XVIII. Java language – basic constructs and comparison with C++.
Credit requirements
The main emphasis in this course is made on practical use of C++ language. After taking this course students are expected to be able to participate in software development projects where object-oriented design and development methodology is used.
In order to receive credit for this course students have to do the following:
1. In the course of semester to develop 2 practical projects using C++ language; to demonstrate the programs, to be able to comment on program sources.
2. To prepare a presentation on some issues of C++ language or object-oriented development.
3. In the course of the final oral examination to be able to answer 1-3 questions (depending on the quality of fulfilling the first 2 requirements).
Literature
1. B.Stroustrup. The C++ Programming Language. Addison-Wesley, 1991.
2. R.Lafore. Object-oriented Programming in C++. Waite Group Press, 1995.
3. B.Meyer. Object-oriented Software Construction. Prentice Hall, 1988.4. A.Eliens. Principles of Object-oriented Software Development. Addison-Wesley,
1995.
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Algorithmic Methods in Artificial Intelligence
Author: Juris Vīksna, Dr.sc.comp.Volume: 4 credits, 64 hoursSemester: Testing form: examinationPrerequisites: noneCourse group:
Abstract
Course is an introduction in the basic notions and concepts of Artificial Intelligence, with a special accent on these Artificial Intelligence problems that have well developed algorithmic methods for their solution. In addition it gives
an overview of two programming languages LISP and PROLOG that are especially convenient for the solving of Artificial Intelligence problems.
Contents
1. Brief overview of problems covered by Artificial Intelligence.2. State space representation. General state space search algorithms.3. Heuristic functions. A* algorithm.4. Admissible algorithms. Admissibility of A* algorithm.5. Optimal algorithms. Optimality of A* algorithm.6. Decomposition space representation. AND/OR graphs.7. Decomposition space search algorithms. AO* algorithm.8. Admissibility of AO* algorithm.9. AND/or graphs for game representation. Search algorithms.10. Pruning method. ALPHA-BETA algorithm, it’s efficiency.11. (In parallel with 1-10.) Overview of LISP programming language.12. Propositional and predicate logics. Reduction of Artificial Intelligence problems
to satisfiability of logical formulae.13. Methods of proving satisfiability of propositional logic formulae. Davis-Putnam
method, resolution method.14. Methods of proving satisfiability of predicate logic formulae. Corresponding
generalizations of Davis-Putnam method and resolution method. Application-oriented modifications of these methods.
15. (In parallel with 12-14.) Overview of LISP programming language.
Requirements for credit
During the course students need to write several (usually 3) programming assignments in LISP and/or PROLOG programming languages, related to particular Artificial Intelligence problems. Course ends with an exam. Approximately 60-70% of final grade depends from grades in programming assignments, approximately 30-40% from grade in final exam.
Literature
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1. M. Genesereth, N. Nilsson Logical foundations of Artificial Intelligence. Morgan Kaufmann Publishers, Inc., 1989.
2. N. Nilsson Problem-Solving Methods in Artificial Intelligence. McGraw Hill Book Company, 1971. (Exists translation in Russian).
3. G. Luger, W. Stubblefield Artificial Intelligence and the Design of Expert Systems. The Benjamin /Cummings Publishing Company, Inc., 1989.
4. R. Shinghal Formal Concepts in Artificial Intelligence. Chapman & Hall Computing, 1991.
5. M. Davis, E. Weyuker Computability, Complexity and Languages. Academic Press, Inc., 1994.
6. I. Bratko Prolog Programming for artificial Intelligence. Addison-Wesley Publishing Company, 1989. (Exists translation in Russian).
7. E. Hyvönen, J. Seppänen, LISP Maailma. Kirjayhtymä Helsinki, 1986. (Exists translation in Russian).
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Algorithms, Automata and Formal Languages I
Author professor Rūsiņš Mārtiņš Freivalds , Dr. hab. math. Volume 2 credits, 32 hoursSemester Testing form written examinationPrerequisites noneCourse group
Abstract
Programs are formalized descriptions of algorithms suitable for needs of specific computing devices. Grammars are useful tools to describe the syntactical correctness of programs. The course is designed for preparing the students to deep understanding of the programming courses. We consider finite automata recognizing languages, finite automata computing functions, formal grammars and languages generated by them. The most essential part of the course is exercises and more difficult problems on the course material
Content
The peculiarity of this course is the fact that the students already know all the needed definitions and most of the theorems from the Bachelor Program of Computer Science in the University of Latvia. During this course the students solve problems. To solve these problems, the students either construct programs for the specified automata or machines or prove impossibility of such programs
1. Finite automata and regular languages
a) Hierarchy of grammars and languages
b) Regular languages
c) Context-free languages
2. Finite automata
a) Finite automata recognizing languages
b) Finite automata computing functions
c) Pumping lemma
3. Pushdown automata
a) Pushdown automata recognizing languages
b) Pushdown automata computing functions
c) Pumping lemma
Requirements
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In the result the students are required to be able construct programs for the automata and machines under consideration, to construct formal grammars for the languages considered in various programming courses of the Master Program of Computer Science in the University of Latvia.
The exam takes place in a written form. The student is required to solve in 2 hours 3 problems of the content and difficulty as in Chapters 1,2,3 of the textbook [1].
Literature
1. Eitan Gurari. An Introduction to the Theory of Computation. Computer Science Press, 1989.
2. Carl H. Smith. A Recursive Introduction to the Theory of Computation. Springer-Verlag, 1994.
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Algorithms, Automata and Formal Languages II
Author professor Rūsiņš Mārtiņš Freivalds, Dr. hab.math. Volume 2 credits, 32 hoursSemester Testing form written examinationPrerequisites Algorithms, automata and formal languages, 1Course group
AbstractTheory of Computation (as it is understood nowadays) tries to find out the reasons why some problems are so hard to solve by computers. This field, virtually non-existent only 20 years ago, has expanded tremendously. No course and no book can be comprehensive now. We consider the results and the methods which can be presented clearly and relatively simply, and which can be viewed as central for the theory.We consider deterministic, nondeterministic and probabilistic Turing machines and parallel machines of various kinds. Complexity of the computation process is considered in terms of the running time, the memory size (space) and other complexity measures. The most essential part of the course is exercises and more difficult problems on the course material
ContentThe peculiarity of this course is the fact that the students already know all the needed definitions and most of the theorems from the Bachelor Program of Computer Science in the University of Latvia. During this course the students solve problems. To solve these problems, the students either construct programs for the specified automata or machines or prove impossibility of such programs.The course is supposed to be an immediate continuation of the course "Algorithms, automata and formal languages, 1"
1. Turing machines
a) Deterministic Turing machines
b) Nondeterministic Turing machines
c) Universal Turing machines
d) Undecidable algorithmic problems
e) Post Correspondence Problem
2. Complexity of computation
a) Time complexity
b) Space complexity
c) Polynomial time and the problem P=NP?
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d) NP-complete languages
e) PSPACE and NPSPACE-complete languages
3. Probabilistic Turing machines
a) Probabilistic Turing machines recognizing languages
b) Probabilistic Turing machines computing functions
4. Parallel algorithms and machines
a) Parallel RAM machines
b) Circuit complexity and the complexity of Parallel RAM machines
Requirements
In the result the students are required to be able construct programs for the automata and machines under consideration, to construct formal grammars for the languages considered in various programming courses of the Master Program of Computer Science in the University of Latvia.
The exam takes place in a written form. The student is required to solve in 2 hours 3 problems of the content and difficulty as in Chapters 4,5,6,7 of the textbook [1].
Literature
1. Eitan Gurari. An Introduction to the Theory of Computation. Computer Science Press, 1989.
2. Carl H. Smith. A Recursive Introduction to the Theory of Computation. Springer-Verlag, 1994.
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Business Basics
Author Jānis Āboltiņš, Dr. EconomyVolume 2 credits, 32 hoursSemesterTesting form written examinationPrerequisites noneCourse group
AbstractThe ability to understand business activities ensures that people of all qualifications can sell their professional services efficiently, develop their qualifications accordingly to the requirements of the job market and thereby insure their well-being. The course discusses the basic notions of business, it analyses and shows with various examples the possibility of successful start of business activities. The goal is to show a way of selling professional services both in small and in large enterprises. Course gives a notion of a correct business activities, what are its advantages and risk, how to manage an enterprise or a working group in order to reach some goal.
ContentsDuring the course students are given an opportunity to acquire the basic knowledge about business, macroeconomics, building and managing an enterprise, market analysis and the choice of the goods to sell. The notions of macroeconomics are viewed upon as they help or hinder the economic development. The mechanism of pricing, tax policies, money policies are discussed along with their influence to the market and business activities. The basics of business are learned as students analyze some particular (imaginary or assumed) business process and go through the following steps:1. Characteristics of an enterprise
1.1. Its philosophy.1.2. Its goals.1.3. Its legal status.1.4. Its owners.1.5. Its structure and employees.1.6. Its location and communications.
2. Products and services of an enterprise2.1. The description of the product or the service.2.2. Technology.
3. Market analysis.3.1. The comparative analysis of a product.3.2. The analysis of competitors.3.3. Marketing description.3.4. Risk analysis.3.5. Samples of finance calculations.
Credit requirementsWrite and defend the business plan of an assumed (imaginary) enterprise.
Literature
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1. Ēriks S. Sīgels et al Biznesa plāna ceļvedis. “Pētergailis”, Rīga, 1994. 2. Colin Barrow, Robert Brown, Liz Clarke, The business growth handbook. Kogan
Page, 1992. 3. А. Хоскинг. Курс предпринимательства. Москва, 1993.
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Business Modeling Languages and Tools - a CASE Study
Author docent Audris Kalniņš, Dr. hab.sc.comp.Volume 4 credits, 64 hoursSemester Testing form examinationPrerequisitesCourse group
Abstract
The objective of the course is to develop skills in business process modeling, using the business modeling language GRAPES-BM as a basis. The main components of the syntax and semantics of GRAPES-BM are being taught, along with typical examples of business system modeling, both for purposes of Business Process Reengineering (BPR) and requirements definition during IS design. Principles of business system simulation and the corresponding facilities in GRAPES-BM are also taught. Students have to develop skills in using the BPR tool GRADE-BM which supports the GRAPES-BM language. The course grading is based on an individual course project - an example of a business system model of certain size.
Content1. Introduction
The main goals of business system modelingThe business modeling languages The family of GRAPES languages
2. The main concepts of GRAPES-BM languageTasksEventsTriggering conditionsDecisionsBusiness process diagram
3. Description of organization structure (ORG diagram)The elements of organization structure and their propertiesThe relationships between elementsPerformer specification in tasks
4. The description of events and timers (ET)5. Task details
The description of additional propertiesTD diagramData attributes
6. Business model of a system and model tree.7. Business process structuring8. Semantics of business process for modeling9. The concept of transaction10. The principles of creating good business models11. Use of data in modeling and simulation
Data types and their definitionExpressions
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Use of data in decisions, in durations etc.Event data settingDefining loopsUse of event data
12. The main basic principle of simulation in GRAPES-BMLoad generatorsSpecification of random values in decisions and durationsTransactions in simulation
13. Statistics in GRAPES-BMDefault statisticsUser defined attributes of tasks for statisticsCalculation of task costsEstimation of results in simulation.
14. The main principles of GRADE Modeller ToolThe graphical editorFacilities for business model developmentUse of simulator and animatorDebugging and testing of an “executable” business model
15. GRAPES as a design languageER model, its connection with class diagramSystem modelingCO diagram, TO table, PD diagram as pseudocodeTransition from business model to system model.
Requirements
The students are required to develop a business model of a system and perform its simulation. The assessment of this work will be the basis for exam.
Literature
1. J.Bārzdiņš, J.Tenteris, Ē.Viļums. Biznesa modelēšanas valoda GRAPES-BM un tās
lietošana, LU MII/Dati,1997.2. GRAPES-BM Language Reference Manual, Infologistic, 1997.
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Business Process Reengineering
Author docent Audris Kalniņš, Dr. hab.sc.comp.Volume 4 credits, 64 hoursSemester Testing form examinationPrerequisites course “Business Modeling Languages and Tools - a CASE
Study” Course group
Abstract
The objectives of the course are to teach the basic principles of BPR, the languages used to formalize the BPR concepts and typical examples of BPR in business systems. First, the basic notions, the goals to be achieved by BPR and some typical methodologies are explained. Then the use of business process modeling in BPR, the role of as-is and to-be models is described. Several most typical languages for business process modeling are briefly introduced, their comparison to GRAPES-BM is made. A number of typical BPR examples in various business system areas are considered. Logical analysis and numerical evaluations by means of simulation of reengineered systems are demonstrated on these examples.
Content
1. IntroductionGoals of Business Process Reengineering Basic concepts of BPR
2. The most popular BPR methods ( from business point of view)The Hansen process classificationThe Hant process representation
3. Business process modelsThe role of business process models in BPRExisting (as-is) system modelsDesired (to-be) system models
4. The most typical languages for business system modelingIDEF series of languagesARISEXTENDThe comparison of business system modeling languages
5. The most typical examples of business system reengineeringOffice systemsDevelopment and testing of softwareManufacturing systemsService systems
6. Analysis of examples: BPR goals, the used methods, the created models7. The role of simulation in BPR8. The comparison of simulation tools (GRADE-BM, EXTEND etc.)
Requirements
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The students are required to develop an example of business system reengineering. The models of this example must be in one of the given languages. The students must give the estimation of reengineering success. The assessment of this work will be the basis for exam.
Literature
1. G.A.Hansen. Automating Business Process Reengineering, Prentice Hall, 19972. V. Daniel Hunt. Process Mapping : How to Reengineer Your Business Processes. John Wiley & Sons, January, 19963. J.Bārzdiņš, J.Tenteris, Ē.Viļums. Biznesa modelēšanas valoda GRAPES-BM un tās lietošana, LU MII/Dati,1997.
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Compilers
Author: docent Andrejs Auziņš, Dr.sc.comp.Volume: 4 credits, 64 hoursSemester: Testing form: examinationPrerequisites: noneCourse group:
Abstract:
Lexical analysis, Symbol Tables, Parsing, Syntax-directed translated, Type checking, Run-time organization, Intermediate Code Generation, Code Optimization.
Contents
Grammars and formal languages, finite automata, push-down automata. Syntax graphs. Lexical analysis. .Syntax analysis. Top-down parsing, LL-parsers, FIRST and FOLLOW sets. Recursive descent method. Bottom-up parsing. LR- parsers. Construction of LR parser tables. Error handling. Syntax - directed translation. Attribute grammars. Semantic analysis. Intermediate code representation. Code generation. Run-time organization, memory management. Register allocation, peep-hole optimization. Global optimization. Compiler design tools. Lex & Yacc. RIGAL.
Literature.
1. Aho, Sethi, Ullman. Compilers. Addison-Wesley, 1986.
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Computer Graphics
Author: docent Paulis Ķikusts, Dr.mat.Volume: 4 credits, 64 hoursSemester: Testing form: examinationPrerequisites: noneCourse group:
Abstract
The course is the higher part of a wider two-level course for bachelor and master degrees. The aim of this part is to get deeper knowledge of the main questions of computer graphics. The approach is characterized by essentially mathematical trend and its principal thesis is "image synthesis as a synonym of computer graphics".
The course begins with the lectures on image synthesis, image perception, informative content of images, and mathematical principles of color theory. In the continuation the seminar-like lessons about the basic chapters of the textbook are held.
Simultaneously with learning the theoretical questions each student makes computer program rendering the scene of hierarchical spatial objects and writes an essay on the individually chosen additional topic.
Contents
Part I -- lectures:1. The role of analytical and computational geometry in computer graphics
- image synthesis as a task of geometric calculations,- mathematical questions of graphic editors.
2. Vector calculus in plane and space- different vector products,- calculation of trigonometric functions of angles between vectors,- the normal vectors of parametric curves and surfaces,- examples of more complex applications of vector calculus.
3. Construction and informative content of the image built by computer- definitions of the image and related concepts,- important hardware elements of raster graphics,- information path from computer video memory to the viewer.
4. Questions of image perception- human visual perception process,- features of sight, optical effects,- Mach bands and their disturbing appearance.
5. Analysis of the informative content of a raster image- reconstructing a continuous image function by the raster hardware,- elements of sampling theory,- perfect sampling, reconstruction, and anti-aliasing.
6. The basic principles of synthesis of raster images in computer graphics- a survey of 2D graphic primitives,
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- the means of image coding and description,- the common structure of scenes to be visualized,- conditions for visual realism.
7. Color palette in basic operations with the structures forming raster images- BitBlt command and raster operations,- advantages and disadvantages of using the color palette,- image effects with the color palette.
8. Basic algorithms for scan converting 2D graphic primitives- Bresenham's algorithm for scan converting line segments,- scan converting line segments in antialiasing technique,- Liang-Barsky line-clipping algorithm,- methods for plotting curves.
9. Calculation of planar projections of spatial objects- classification of planar projections,- mathematical expressions of parallel and perspective projections,- relations among the world, camera and image coordinates.
10. The way of achieving visual realism- plotting single-valued functions of two variables,- Catmull's recursive subdivision method with z-buffer,- Lambert's illumination law.
11. Foundations of the mathematical theory of color perception- formal definition of color,- identically looking light of different spectral distribution,- metamerism phenomenon,- the basic properties of color spaces,- the cone of visible colors and chromaticity diagram.
12. Principles of color reproduction- color coordinates in the system of primary light sources,- color gamut of finite number of primary light sources,- color coordinate systems,- subtractive color synthesis.
Part II -- seminars about the basic chapters of the textbook [3, 4]: 1. Introduction 2. Programming in the Simple Raster Graphics Package (SRGP) 3. Basic raster graphics algorithms for drawing 2D primitives 4. Graphics hardware 5. Geometrical transformations 6. Viewing in 3D 7. Object hierarchy and Simple PHIGS (SPHIGS)
Part III -- individual computer program for rendering hierarchical 3D objects
Part IV -- essay on the individually chosen additional topic
Requirements
To pass the examination it is necessary:1) to answer in written form ten questions concerning the topics of thelectures and the textbook,2) to demonstrate and defend an individually written computer program forrendering hierarchical 3D objects,
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3) to present an essay on the individually chosen additional topic ofcomputer graphics.
Bibliography
1. G.A.Agoston. Color Theory and Its Application in Art and Design -- Springer,1987.2. A.K.Jain. Foundations of Digital Image Processing -- Prentice Hall, 1989.3. J.D.Foley, A.van Dam, S.K.Feiner, J.F.Hughes. Computer Graphics,Principles and Practice -- Addison-Wesley, 1993.4. J.D.Foley, A.van Dam, S.K.Feiner, J.F.Hughes, R.L.Phillips. Introductionto Computer Graphics -- Addison-Wesley, 1994.
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Computer Networks I
Author: docent Guntis Bārzdiņš, Dr.sc.comp.Value 4 credits, 64 hoursSemester Testing form examinationPrerequisites noneCourse group
Abstract
The goal of the course to familiarize students with the classic data networking theory from early days to nowadays. The course is primarily theoretical, but there are also several home assignments where Internet has to be used. Course covers virtually all data networking technologies, including Local Area Networks, Wide Area Networks (Modems, Wireless links, Fiber links) and various network applications and their principles. The course is organized around classic seven layer ISO OSI reference model, where various data transmission issues are grouped in physical, data link, network, transport, session, presentation, and application layers.
Course content
Following are main topics discussed in the course:
1. Various types of Data networks: LAN, MAN, WAN.2. Benefit of using layered Data networking model. ISO OSI reference model.3. Maximum data transmission speed through limited frequency channel. Nyquist un
Shannon formulas.4. Characterization of data transmission media: magnetic, twisted pair, coax cable,
fiber, radio.5. PCM and T1, E1 transmission standards6. Synchronous and Asynchronous data transmission7. Use of Connection Oriented and Connectionless principles in Data networks8. Principles of ISDN networks9. Principles of X.25 networks10. Principles of Frame Relay networks and ATM networks11. MAC sub-layer, ALOHA and CSMA/CD12. MAC sub-layer, ring topologies: Token Ring, FDDI13. Data link: bit and byte level framing techniques, synchronization14. Data link: Forward error correction, Humming code15. Data link: Error detection, CRC16. Data link: Sliding windows protocol17. Various routing algorithms, addressing principles at network layer18. Concepts of Repeater, Bridge, Switch, Router – their differences19. Transport layer, quality of service parameters. Need for error correction in
transport and data link layers.20. Transport layer, Connection establishment and Disconnection. The “two
armies” problem.21. Session layer, RPC usage principles.22. Presentation layer, Data compression principles
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23. Presentation layer, Data encryption principles24. Four layers of TCP/IP protocol suite, main protocols in each layer25. Ethernet/IEEE 802.3 frame format and addressing26. SLIP and PPP protocols27. ICMP – main uses28. Format of IP packet, concept of MTU and IP fragmentation29. IP addressing, subnet mask, routing. CIDR concept30. ARP and RARP protocols31. IP routing table, dynamic routing protocols, RIP32. Concept of Autonomous System, principles of BGP routing protocol33. UDP protocol, segment format, port concept in TCP/IP34. TCP protocol, segment format, connection establishment and disconnection,
socket concept35. Domain Name System principles (DNS)36. Simple Mail Transfer Protocol principles (SMTP)37. Simple Network Management Protocol principles (SNMP)
Condition to receive a credit
After completing the course, students are expected to understand the principles of all above mentioned data networking issues and their relationship. Students should understand the principles of various practically used data networking standards.
To complete the exam it is necessary to:1. During the course to make a presentation about one of the data networking
themes offered by the teacher,2. During Exam to answer 3 randomly selected questions from themes listed
above, as well as be able to answer related questions on the spot.
Literature
1. Andrew S. Tanenbaum, Computer Networks, Third Edition, Prentice Hall, 813p., 1996
2. Douglas E. Comer, Internetworking with TCP/IP, Volume 1: Principles, Protocols, and Architecture, Third Edition, Prentice Hall, 613p., 1995
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Computer Networks II
Author: docent Guntis Bārzdiņš, Dr.sc.comp.Value 4 credits, 64 hoursSemester Testing form examinationPrerequisites Computer Networks, Part 1Course group
Abstract
The goal of this course is to provide deeper knowledge about Data Network protocols which currently are widely used. The primary focus is on TCP/IP protocol suite and its use in the Internet and Intranets. Considered are also current trends in Local Area Network design, use of switched networks, selection of operating system/hardware for various tasks. This course relies on the theoretical background of course “Data Networks, Part 1” and provides deeper understanding of networking issues as they appear in practically used data network protocols. (TCP/IP, IPX, NetBIOS, Frame Relay, ATM, ISDN). The course has both theoretical part, and practical part with labs related to setting up a network.
Course content
Following are main topics discussed in the course:
1. Fixed data transmission media: fiber, coax cable, twisted pair2. Wireless data transmission: analogue, spread spectrum, satellite communications3. Synchronous data transmission: HDLC, PPP, LAP-B.4. Asynchronous data transmission: SLIP, PPP5. Authentication protocols PAP and CHAP6. Multi-access data transmission media: Ethernet CSMA/CD, ARP, Token Ring7. ATM basic principles, LAN emulation.8. Concepts of Bridge and Switch. Virtual LAN concept. 9. Addressing principles in IP networks, address and mask: 10. Format of IP packet11. IP routing tables. Static routes, default route, proper use of netmasks12. Dynamic IP routing protocols: RIP, OSPF, BGP13. ICMP message types, their use in PING and TRACEROUTE utilities14. SNMP protocol, network management principles 15. Transport layer protocols TCP and UDP, their segment formats16. Concept of Port and Socket in TCP/IP. Examples of applications and their well-
known port numbers17. DNS design and operation principles18. SMTP, POP protocol principles for e-mail delivery19. HTTP protocol, its comparison to FTP protocol20. HTML language principles21. JAVA application, applet, script22. NetBIOS operation and transport over IP23. Novell IPX basic principles
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Condition to receive a credit
After completing the course, students are expected to understand the principles of all above mentioned data networking issues and their relationship. Students should understand the principles of various practically used data networking standards, be able to design simple data networks, create simple network applications.
To complete the exam it is necessary to:1. During the course to make a presentation about one of the data networking
themes offered by the teacher and also to complete a small practical project related to data networks,
2. During Exam to answer 3 randomly selected questions from themes listed above, as well as be able to answer related questions on the spot.
Literature
1. W.Richard Stevens, TCP/IP Illustrated, Volume 1, Addison-Wesley, 576p., 19952. Douglas E. Comer, Internetworking with TCP/IP, Volume 1: Principles,
Protocols, and Architecture, Third Edition, Prentice Hall, 613p., 19953. Andrew S. Tanenbaum, Computer Networks, Third Edition, Prentice Hall, 813p.,
1996
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Database Fundamentals IAuthor docent Kārlis Podnieks, Dr.sc.mat.Volume 2 credits, 32 hoursSemesterTesting form examinationPrerequisites knowledge of master course of data basesCourse group
Abstract
Object-oriented databases. Distributed databases. Deductive databases. Database integrity, security and reliability. Concurrency control. Query processing.
Course content
1. Object-oriented databasesObject support in current relational database systemsComplex object modelImplementation techniques for complex objectsSupport of object identity
2. Distributed databasesDistributed database capabilitiesObjectivesIssuesArchitecturesHomogeneous DDBMSHeterogeneous DDBMSDatabase machines
3. Deductive databases Rule definition language for databasesDeductive query processing and modelingRecursive query processingDeductive DBMS architectures.
4. Integrity, security and reliabilityDefinition of integrity constraintsAnalysis of integrity constraintsData integrity enforcementData securityReliability: basic concepts, algorithms, and implementation of updates
5. Concurrency controlCharacteristics of conflict-free executionInitial timestamp-ordering algorithms
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Optimistic algorithmsTwo-phase locking algorithmsDeadlock solutions
6. Query processingObjectivesParameters influencing query processingIssues in designing a query processorQuery decompositionAlgebraic restructuring methodsQuery optimization.
Literature
G.Gardarin, P.Valduriez, Relational Databases and Knowledge Bases, Addison-Wesley, 1989.
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Database Fundamentals IIAuthor docent Kārlis Podnieks, Dr. sc. mat.Volume 2 credits, 32 hoursSemesterTesting form examinationPrerequisites knowledge of master course of data basesCourse group
AbstractThe SQL language. Why it is important. Language constructs and their syntax. Views. Embedded SQL. Critique of SQL.
The Object Database Standard ODMG 2.0. Object model. Object definition language (ODL). Object interchange format (OIF). Object query language (OQL) and its comparison with SQL.
Course content
1. SQL languageWhy SQL is importantBase tables, constraintsPrivilegesPrimary and foreign keysTransaction management, COMMIT, and ROLLBACK operationsCursors, ORDER BY optionCursor OPEN, FETCH, UPDATE, DELETE and CLOSE operationsSELECT operations, INSERT operations Non-cursor UPDATE and DELETE operations View definition syntaxView retrieval and update operation restrictionsCheck option
2. SQL module languageSyntaxProcedures, parameters, indicator-parametersEmbedded SQL
3. Critique of SQL
4. Object database standard ODMG 2.0.Architecture.. Object model.Objects and literals. Type hierarchy: interfaces and classes. Locking and concurrency control. Transactions.
5. Object specification languagesObject definition language (ODL).Object interchange format (OIF).
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6. Object query language (OQL)Principles. Comparison with SQL.Query input and result. Dealing with object identity.Path expressions. NULL values.Object method invoking. Polymorphism.Operator composition.
Literature
1. C. J. Date, A Guide to the SQL Standard, Addison-Wesley, 1989.2. The Object Database Standard: ODMG 2.0. Morgan-Kaufmann, 1997
Web links
SQL Standards Home Page: Object Data Management Group: Object Management Group (ONG, CORBA)
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Data Protection and Cryptography
Author professor Rūsiņš Mārtiņš Freivalds, Dr. hab. math.Volume 2 credits, 32 hoursSemester Testing form examination Prerequisites noneCourse group
Abstract
Traditional (up to World War 2) systems of information encryption. disadvantages of the traditional systems. Discoveries of the Complexity Theory enabling the "Public-key" systems. Knapsack type systems. RSA algorithms. Poker and other card games by telephone. Secret vote by telephone. Other surprising protocols of information exchange. Verifiable proofs disclosing no information. How complicated and how secure is data protection.
Contents
1. CAESAR monoalphabetic cryptosystem.
2. CAESAR cryptosystem with keywords.
3. Affine cryptosystem.
4. Hill cryptosystem.
5. Cryptosystem PLAYFAIR and its generalizations.
6. Usage of statistics in cryptoanalysis of monoalphabetic systems.
7. Polyalphabetic cryptosystems.
8. Rotor cryptosystems.
9. DES (Data Encryption Standard).
10. Principles of Public-key cryptography.
11. Cryptosystem RSA.
12. Main notions and results in Congruence Theory.
13. Legendre symbol.
14. Jacobi symbol.
15. A randomized algorithm for recognition of primality.
16. Digital signatures.
17. Card games over telephone.
18. Generation of random numbers.
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19. NP-complete sets.
20. Zero-knowledge proofs.
21. Protocol protection.
Requirements
The examination takes place in a written form. The student is required to prove theorems and to solve problems. The student is to understand deeply that: data protection and small complexity of computation mutually exclude one another; in practice compromises are inevitable. the modern Computational Complexity Theory provides tools both for data protection and for cryptoanalysis.
The student is to be able to solve problems of the following kind: Encrypt the given plaintext using one of the considered cryptosystems. Decode the given cryptotext encoded in the given cryptosystem. Given letter and word frequency tables, decrypt the given cryptotext in the Hill cryptosystem. Solve the given first or second degree congruence. Compute Jacobi symbol legendre (17) and explain the result. Find out
3whether or not the number 1997 is prime.
Literature
1. A. Salomaa. Public-Key Cryptography. Springer-Verlag, 1990
2. G. Brassard. Modern Cryptology. Springer-Verlag, 1988
3. R. DeMillo, G. Davida, D. Dobkin, M. Harrison, R. Lipton. Applied Cryptology, Cryptographical Protocols and Computer Security Models. American Mathematical Society, 1983
4. A. Konnnheim. Cryptography: A Primer. John Wiley and Sons, 1982
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Foundations of Specification Languages
Author: docent Kārlis Čerāns, Dr.sc.comp.Volume: 4 credits, 64 hoursSemester: Testing form: ExaminationPrerequisites: noneCourse group:
Abstract
The course is devoted to the notion of formal specification and a series of important models and systems for presenting formal specifications. The foundations of program module input/output behaviour specification are considered, as well as alternative approaches to mathematical definition of data types (main principles of languages ACT ONE, LARCH, B, Z, VDM). A substantial part of the course is devoted to a number of wide spread specification formalisms for reactive systems (CCS, LOTOS, automata-based models, temporal logics, Petri Nets).
Contents
1. The notion of specification, its role in the software engineering process. Formal specifications, relations between specification and implementation. Hierarchic and modular specifications.
2. Specification of a programming module (procedure). Partial and total correctness specifications. Overview of Hoare logic.
3. Abstract data types, their use in program system specification.
3.1. Functional-defined data types (constructive data types, algebraic data types (ACT ONE), the LARCH language for two-tiered system specification on the basis of weak semantics).
3.2. Model-based data and system specification languages. The B language for specification and analysis of abstract machines. The Z and VDM languages, their basic constructions and examples.
4. Languages of reactive system specification.
4.1. Algebras of parallel processes. Labeled transition systems. Process algebra CCS. Strong and weak bisimulation equivalencies. Specification language LOTOS.
4.2. Elements of general parallel process theory. Protocol, failures and bisimulation equivalencies, their comparison for non-deterministic and deterministic systems.
4.3. Automata on infinite words.
4.4. Temporal logics, their main constructions and use in program property description. Classical temporal logic FOLTL. The temporal logic TLA.
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4.5. Petri Nets, their basic mathematical model and main analysis problems. System specification by means of coloured Petri Nets.
4.6. Automata with clocks. Example of specification of Audio control protocol.
Requirements
Understanding basic notions related with considered specification formalisms, recognizing the main specification construction principles and ability to explain the differences between various considered models. One must be able to use the obtained knowledge to solve simple model exercises related with the considered specification models.
Literature
1. H.Ehrig, B.Mahr. Fundamentals of Algebraic Specification 1. EATCS Monographs on TCS – 6. Springer Verlag, 1985.
2. J.Guttag, J.Horning. Larch: Languages and Tools for Formal Specification, Springer Verlag, 1993.
3. J.B. Wordsworth. Software Engineering with B. Addison-Wesley, 1996.
4. J.B. Wordsworth. Software Development with Z. Addison-Wesley, 1992.
5. C.B. Jones. Systematic Software Development using VDM. Prentice Hall, 1990.
6. R. Milner. Communication and Concurrency. Prentice Hall, 1989.
7. Handbook of Theoretical Computer Science, vol. B (Formal Models and Semantics), The MIT Press/Elsevier, 1990.
8. L. Lamport. The Temporal Logic of Action. DEC SRC TR-79, 1991.
9. J.L. Peterson. Petri Net Theory and the Modeling of Systems. Prentice Hall, 1981.
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Information Systems Design
Author docent Kārlis Podnieks, Dr. sc. mat.Volume 2 credits, 32 hoursSemester 1st Testing form examinationPrerequisites knowledge of master course of data basesCourse group
Abstract
Two paradigms of systems development: the traditional paradigm and the object technology. Data flow diagrams. Bridge methodology. Enterprise modeling techniques. Joint Application Development (JAD). Rapid application development and prototyping. Designing system data structures, behaviors and interfaces. Documenting design specifications. System test and installation. Post-implementation activities.
Contents
1. An Overview of systems developmentThe process of system development: two paradigms Data flow diagramsBridge methodologyBenefits of object technology and modeling techniques
2. Preliminary investigation and analysisSystems development equals planned organizational changeEnterprise modeling techniquesEnterprise analysisProblem definition and feasibility analysisJoint Application Development (JAD)
3. Iterative analysis, design, preliminary construction, and reviewRapid application development and prototypingAnalyzing and designing system data structuresAnalyzing and designing system behaviorsAnalyzing and designing system interfacesDocumenting design specifications
4. Final construction, testing, installation, and reviewConstructing and verifying the data componentConstructing (acquiring) and verifying the data componentConstructing and verifying documentationSystem test and installationPost-implementation activities
Literature
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Sandra Donaldson Dewitz. Systems Analysis and Design and the Transition to Objects, Mc Graw Hill, 1996.
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Mathematical Logic in Computer Science
Author: docent Jānis Cīrulis, Dr.sc.comp.Volume: 2 credits, 32 hoursSemester: Testing form: examinationPrerequisites: noneCourse group:
AbstractThe intention of the course is to initiate the students in a few logical applicable (or created for applications) in computer science. Chosen are systems based on modal logic. The three main topics are: modal propositional (and, briefly, predicate) logic, temporal logic and dynamic logic; discussed are syntactic (including formalized proofs, semantical (Kripke structures and their variants), and metatheoretical matters. The possible applications are sketched, but it is not a purpose of the course to go deep into them.
ContentsI Modal logic1. Sources of modalities in computer science.2. Language of modal logic (syntax).3. Kripke frames and forcing.4. Semantic of modal logic.5. Tableau proofs.6. Properties of modal operators.7. Results on soundness and completeness.8. Special accessibility relations.9. Hilbert style axiomatics.10. Modal predicate logic.11 Some specific modal logics.
II Temporal logic1.Classification of program logics.2. Propositional temporal logic---syntax and semantics.3. Means of inference in temporal logic.4. Tableaux in temporal logic.5. Metamathematical results on temporal logic.6. Additional temporal operators.7. Branching time logic.8. Applications: program correctness etc.
III Dynamic logic1. Propositional dynamic logic (PDL)---syntax and semantics.2. Properties of program operators.3. Inference in PDL.
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4. Metamathematical results.5. Variants of PDL.6. First-order dynamic logic---syntax and semantics.
IV Micelania
To get the credit for the course, during the term a student has to pass, in writing, several tests. Every test includes both theoretical questions and problems; each of these is evaluated by a certain number of points. The score 35% provides the minimal positive grade (... 4), the grade increases by 1 with any further 5%.
Literature:1. Ben-Ari, Mathematical Logic for Computer Science, Prentice-Hall, 1993.2. Emerson, Temporal and modal logic. In: Handbook of Comput. Sci. II, Elsevier,
1990 (Chapt. 16).3. Kröger, Temporal Logic of Programs, Springer, 1987.4. Kozen, J. Tiuryn, Logics of Programs, In: Handbook of Comput. Sci. II, Elsevier,
1990 (Chapt. 14).5. Nerode, Some lectures on modal logic. In: Logic, Algebra and Computation,
Springer, 1991, 281--334.6. Nerode, R.A. Shore, {Logic for Applications}, Springer, 1993.7. Pratt, Application of modal logic to programming, Studia Logica 39 (1979), 258--
274.
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Metamodels and Formal Specifications
Author professor Jānis Bārzdiņš, Dr. hab.sc.comp.Volume 4 credits, 64 hoursSemesterTesting form examinationPrerequisites course “Object-oriented analysis and modeling”Course group
AbstractCourse discusses both the traditional and the advanced methods of language formalization. The building of metamodels and their use to define the graphical syntax and semantics of languages is also discussed. The traditional ways to define semantics of programming languages are shown: attribute grammars (translation semantics), Vienna Definition Method, VDM (operational semantics), Hoare axioms (axiomatic semantics), equality systems (algebraic semantics). Course ends with an overview of other methods of defining semantics, it also briefly discusses the semantics of parallel processes.
ContentsCourse aims at giving a deeper understanding of syntax and semantics of programming languages, it discusses different methods of defining syntax and semantics and shows applications of these formalisms.
1. Metamodels and their usage.2. Semantics of programming languages, overview about different methods of
defining semantics (as well as syntax). 3. Translational semantics.4. Operational semantics.5. Axiomatic semantics.6. Algebraic semantics.7. The notion of the semantics of parallel processes.
Credit requirementsDuring the course students should properly understand the principles of metamodel building and their practical use to define languages and tools of system modeling. Also students should have sufficiently deep knowledge about the most popular methods to define the semantics of programming languages along with the practical use of these methods. To pass the exam a student should:1. To hand in and to defend five big homeworks about the different methods of
semantics definition.2. To give appropriate answers to two arbitrarily chosen theory questions about the
topics mentioned in the course description.
Literature
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1. Rumbaugh J. et al. Object-oriented modeling and design. Prentice Hall, 1991 (Chapters 3,4).
2. Fowler M. UML distilled. Applying the standard object modeling language. Addison-Wesley, 1997.
3. Bourdeau R.H. and B.H.C. Cheng. A formal Semantic of Object model diagrams. IEEE Transactions on Software Engineering, vol. 21, Nr.10, 1995.
4. U.Sarkans, J. Bārzdiņš, A. Kalniņš and K. Podnieks. Towards a metamodel-based universal graphical editor. IMCS, 1997.
5. F.G.Pagan. Formal specification of programming languages. Prentice Hall, 1981 (Chapters 1-4).
6. Watt D.A. Programming language syntax and semantics. Prentice Hall, 1991 (Chapters 1-3, 6).
7. Winskel G.. The formal semantics of programming languages. MIT Press, 1989 (Chapters 1-6, 11).
8. Bachhouse R.C. Program Constructions and Verification. Prentice Hall, 1986 (Chapter 3, Verification).
9. M.J.C.Gordon. Programming language theory and its implementations. Prentice Hall (Chapters 1-3).
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Office Automation
Author docent Māris Vītiņš, Dr.sc.comp.
Course 2 credits, 32 hours
Semester
Testing method examination
Prerequisites noneCourse group
Abstract
The course is made up of four blocks. The course commences with an examination of office automation. This block is based on the text by Andrew Doswell “Office Automation: Context, Experience and Future”. Further we examine the office software package MS Office, in particular MS Word and MS Excel. Following this we look at official correspondence and their design. In concluding the course, an overview of Latvian national standards on information technology and language use in computers is given.
Contents
The aim of the course is to clarify office automation, to systematize and broaden students knowledge of MS Word and MS Excel, to introduce the writing of official correspondence, as well as official Latvian national standards applying to information technology and language use in computers.
I. Office Automation.
A. Organization and Information. Communication.
B. Information Technology.
C. Software.
D. System Performance.
E. Models of the Office.
F. Examples of Different Offices.
G. The Future Office.
II. Office software MS Office.
A. MS Office software components.
B. Text editing using MS Word.
C. Calculations and diagrams using MS Excel.
III. Official Correspondence.
A. Definition, functions, framework and writing of official correspondence.
B. Most often used official correspondence.
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IV. Latvian language and computers.
A. Standards.
B. Computer terminology.
Credit Requirements
At the end of the course students are expected to know office automation, must be able to use MS Word and MS Excel in everyday situations, must be ready to study MS Office in depth, must be able to write necessary everyday correspondence.
Requirements for passing the examination
1. To prepare, hand in and discuss theses (up to 15 min.) about office automation.
2. To prepare, using MS Office components Word and Excel, and hand in 4 documents: official request, CV, contract and calculation (with diagram).3. In the examination to answer 2 theoretical questions on themes mentioned in the course description.
Literature
1. A. Doswell. Office Automation: Context, Experience and Future. John Wiley and Sons, 1990.
2. J.Kalējs. Lietvedības pamati. Biznesa komplekss, 1994.
3. R.Koluža. Darījumraksti. Pētergailis, 1996.
4. V.Skujiņa. Valsts valodas prasmei lietvedības dokumentos. Biznesa komplekss, 1993.
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Operating Systems
Author: docent Juris Strods, Dr.sc.comp.Volume: 4 credits, 64 hoursSemester: Testing form: examinationCourse group:
Abstract
The goal of the lecture course is get students familiar with the basic algorithms of the operating systems. Explanation of basic functions of the operating systems and their implementation is based on the logical model of a computer presented in the lecture course “Computer architecture”. Special attention is paid to synchronization mechanisms on different levels.
Contents
1. General overview and classification of operating systems.2. Architecture of computer systems.3. Operating system structure.4. Processes.5. Process coordination.6. Deadlock.7. Memory management.8. Virtual memory.9. File systems..
RequirementsStudents have to understand the basic principles of structuring and functioning of an operating system and to be ready to study deeper without assistance.
The methods and primitives of interprocess communication must be on the level of practical application.
The principles of virtual memory must be understood to know basic algorithms and their impact on functioning of the whole system.
To pass the exam one should:
1. Successful tests.2. During final test a set of problems on above defined topics must be solved.
Literature1. A.Silberschatz, J.L.Peterson, P.B.Galvin. Operating Szstem Concepts. Addison-Wesley,1991.
2. A.S.Tanenbaum. Modern Operating Systems. Prentice Hall, 1992.
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Oracle Basics
Author: docent Andrejs Auziņš, Dr.sc.comp.Volume: 2 credits, 32 hoursSemester: Testing form: ExaminationPrerequisites: noneCourse group:
Abstract.
The aim of the course is to examine the opportunity to utilize the Designer/2000 BPR tools to analyze and redesign fundamental business processes through management focused techniques.
Contents.
1. Oracle CASE method.
2. Designer/2000 Product Overview.
2.1. Data Diagrammer, Module Logic Navigator, Repository Object Navigator, Server Generator
3. Database Design
4 Procedural server-side logic design
5. Server Generation
6. Maintenance
7. Design Recovery
Literature
1. Oracle Designer/2000 Product Overview //ORACLE 1995.
2. Oracle Designer/2000 A Guide to System Design //ORACLE 1995
3. Oracle Designer/2000 Tutorial //ORACLE 1995
4. Oracle Designer/2000 A Guide to Repository Administration //ORACLE 1995
5. Oracle Designer/2000 A Guide to Developer/2000 Generation //ORACLE 1995
6. Oracle Developer/2000 Forms 4.5 Getting Started Manual //ORACLE 1994
7. Oracle Developer/2000 Forms 4.5 Reference Manual vol.1/vol.2 //ORACLE 1994
8. Oracle Developer/2000 Forms 4.5 Developer’s Guide Manual //ORACLE 1994
9. Oracle Developer/2000 Forms 4.5 Advanced Techniques Manual //ORACLE 1994
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10. Oracle Developer/2000 Reports 2.5 Building Reports Manual //ORACLE 1995
11. Oracle Developer/2000 Reports 2.5 Reports Reference Manual //ORACLE 1995
12. Oracle Developer/2000 Procedure Builder 1.5 //ORACLE 1994
13. Oracle Developer/2000 Forms 4.5 Runtime Manual //ORACLE 1995
14. Oracle Developer/2000 Reports 2.5 Runtime Manual //ORACLE 1995
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Program Testing
Author docent Jānis Bičevskis, Dr.sc.comp.Volume 4 creditsSemesterTesting form examinationPrerequisites noneCourse group
Abstract
Course aims at repeating and enhancing the knowledge about the notions and methods of program testing acquired during undergraduate classes, to understand the theory of automated building of a complete system of tests, and to get acquainted with the most popular tools for program testing. In the first part of the course the traditional methods of testing are presented: structural, functional, control flow, transaction flow, value domain, state transition and data flow testing. In the second part of the course an algorithm to build complete systems of tests is given for various formalizations of programming languages. In the third part of the course various tools for program testing are considered along with their possibilities: regress testing, playback of tests, automated construction of testing models and checking for completeness of testing.
Contents
1. Software testing1.1 Software testing principles1.2 Structured testing1.3 Functional testing1.4 Data flow testing1.5 Transaction flow testing1.6 Domain testing1.7 Syntax testing1.8 Finite state testing
2. Complete test systems construction2.1 Programming languages formalizing 2.2 Complete test systems construction algorithm for base
language 2.3 Extensions of base language and solvability of
construction of complete test systems 2.4 Complete test systems construction implementation 2.5 Complete test systems construction optimization.
3. Testing tools
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3.1 Overview of testing tools 3.2 Regress testing3.3 Capture of test cases 3.4 Playback of tast cases, 3.5 Construction of testing models 3.6 Completeness of testing
Requirements for credit
During the course the main methods of software testing should be practically acquired. The theory of automated building of complete test systems and the most popular tools of testing should be acquired up to their basic ideas, so the students can learn them on their own in case of necessity. To pass the exam, one should: 1. Prepare a 45 minute presentation about one of the methods of program testing.
The report should include the basic ideas of the method and its applications. 2. Get a passing grade in a test on automated building of complete testing systems. 3. Using Internet, collect, analyze and give a presentation on some particular tool of
program testing.
Literature
1. Boris Beizer. Black-Box Testing Techniques for Functional Testing of Software and Systems. John Wiley & Sons, Inc., USA, 1995, 294 p.
2. B.Beizer An overview of testing. Quality Week Europe 1997. Tutorial Notes. Software Research Institute, USA, 1997.
3. A.Auzins, J.Barzdins, J.Bicevskis, K.Cerans, A.Kalnins. Automatic construction of test sets: theoretical approach. Lecture Notes in Computer Science. Vol. 502, Springer - Verlag, 1991.
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Management Information Systems
Author professor Juris Miķelsons, Dr. PhysicsSemesterVolume 96 hours Testing form examinationPrerequisites: noneCourse group
AbstractThe notions of control and management apply to many areas – to genetics, to the control of technological objects and processes, and, finally, to the leading of countries and separate branches of economy. As we are heading towards the Infosociety, reasonable management necessarily involves Information Technologies (IT) and Management Information Systems (MIS). The course shows three application of IT to the management process; discusses the notion of the state of a process (or an object), shows how to choose the parameters characterizing state of a system both in natural sciences and in business and social processes; how to find regularities in the changes of system parameters.
The course aims at giving knowledge about the informative support of management using state-of-the-art IT&T to prepare the specialists for the next step – modeling of the development as done by the Millennium Institute (A nonprofit organization promoting long-term integrated global thinking, 1117 North 19th Street, Suite 900, Arlington, Virginia 22209-1708 USA).
Contents1. The notion of the “state” of the process to be managed.2. The definition of MIS, examples, necessity. The structure of MIS.3. The technical support of MIS technology, software and telecommunication
support. 4. Conceptual questions. Passing decisions. The concept of information.5. Humans as information processors.6. The concept of system. 7. Planning and control.8. The structure of organizations and the subordinated concept of management.9. The management supporting by MIS. MIS for planning, control, decision passing.10. Informative systems (IS) corresponding to intellectual work. 11. Requirements for MIS, auditing MIS, long-term plans for MIS building. 12. The strategy of stating requirements for MIS. Requirements for databases.
Requirements for the user interface.13. IS development, implementation, and the management of IS resources.14. The development of applied IS, their introduction and usage.15. The quality control for IS, the audit of IS. 16. Data sources, data preparation, ensuring data actuality, organization and
management of information resources. 17. Future perspectives of IT&T usage for management support.
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18. The particular examples of IS used by state and local governments, different branches of economy. Implementation, exploitation, control and coordination of such systems.
19. Millennium institute in USA. Modeling country development. Modeling the development of different branches of economy.
20. The policy of Latvia in introducing IT for the support of state and local government functions.
Some parts of the course may change along with the advancement of IT&T application in the state management.
Credit RequirementsGive a presentation about the problems of the course, prepare a written version of the question being analyzed and distribute its copies to other students.Hand in an individual project about the definition of a certain object (e.g. university, school, insurance company, drug store), explain the chosen system parameters, describe the desired state, the program of transition from the current state to the desired one, the necessary financial a/o. means to reach the desired state. The examination consists of 3 questions and the defense of the individual project.
Literature1. Management Information System. Conceptual Foundations, Structure and
Development. Second edition. Gordon B. Davis, Margrethe 693 pages. H. Olson, 1985.
2. Gerald O. Barney, W. Brian Kreutzer, Martha I. Garett, - Managing a Nation. Second edition. The Microcomputer Software Catalog. Institute for 21st Century Studies, 1990.
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Project Management
Author docent Māris Treimanis, Dr.sc.comp.Volume 2 credits, 32 hoursSemesterTesting form written examinationPrerequisites noneCourse group
AbstractThe goal is to acquire the basic knowledge needed by any project manager. Course discusses the following topics: elements of an organization, planning, organizing, management and control. All the topics are exposed from the software project management point of view.
Contents1. Management science, its subject and history.2. The paradigms of contemporary management.3. Motivation.4. Groups and informal organizations.5. Technology.6. Goals, strategy, planning and decision taking.7. The structure of organizations.8. Management via projects.9. Coordination, authority, power and the design of work process.10. Management and manager.11. Organization level and interpersonal communication.12. Control, estimate of productivity and bonus.
Credit Requirements1. Written presentation about a particular topic of project management.2. Passed written examination.
Literature1. David R. Hampton. Contemporary Management, McGraw-Hill, 1981.2. Neal Whitten Managing Software Development Project, John Wiley&Sons, Inc.,
1990. 3. 10th INTERNET World Congress on Management by Projects Proceedings, 1990.
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Program Verification
Author: docent Kārlis Čerāns, Dr.sc.comp.Volume: 2 credits, 32 hoursSemester: Testing form: ExaminationPrerequisites: noneCourse group:
Abstract
The course present mathematical solutions to the program correctness problem. Initially, elements of traditional verification theory are considered, including the notions of partial and total correctness, flow-chart programs, inductive assertion and well-ordered set methods, as well as Hoare logic for verification of structured programs. The second part is devoted to alternative verification methods, including abstract interpretation and positive results regarding possibilities of verification automation.
Contents
1. The problem of program correctness, program testing and verification as different means of dealing with it. The place of verification in software engineering.
2. Elements of traditional verification theory.2.1 Procedure interface specifications. Partial and total correctness assertions.2.2. Flow-chart programs. Inductive assertion method for proving partial correctness assertions. Verification conditions.2.3. Well-ordered sets. Termination proofs for flow-chart programs.2.4. Compositional (axiomatic) method for verification of structured programs(Hoare logic).2.5. Soundness and completeness of verification axiom systems.2.6. Verification of programs with data structures, arrays and procedures.2.7. Example of proving algorithms correct.
3. Algorithmic analysis of programs.3.1. Abstract interpretation (general theory of program analysis).3.2. Algorithmic analysis of extended automata.3.2.1. "Base language" programs (relational automata).3.2.2. Real-time automata.3.2.3. Petri Nets.3.2.4. "Well-ordered" systems (a general structure allowing for automated analysis of extended automata).
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Requirements for a credit
Understanding the main notions and constructions of traditional verification theory (including the main proofs), as well as ability to solve simple verification exercises. In-depth knowledge of algorithmic analysis methods is an alternative requirement to a programming work in traditional verification theory.
Literature.
1. N. Francez. Program Verification. Addison-Wessley, 1992.
2. Z. Manna. Mathematical Theory of Computation. McGraw-Hill, 1974
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Software Quality
Author docent Juris Borzovs, Dr.sc.comp.Volume 2 credits, 32 hoursSemesterTesting form examinationPrerequisitesCourse group
Abstract
Course object is requirements rendered by software industry, i.e., long-term projects demanding big effort and big development team. The course begins with general exploration of quality concept and review of international and national quality system, independently of any specific branch of economy. ISO 9000 group of standards requires that a manufacturing or servicing organization itself must be internally put in order, i.e., there must be implemented and permanently maintained internal quality system. Such a system comprises standards (what must a product or intermediate products be), procedures (how must the product be developed) and controls - managerial and technical mechanisms that forbid to deviate from established production discipline by revealing of non-conformance well in advance. Internal quality system of software producting organization, based on internationally admitted IEEE software engineering standards, is analyzed. During practical exercises, examples of most important software documents are developed.
Content
The main course objective is, relying on software system development methods already acquired in other software engineering courses, to learn ISO 9000 quality system elements at a level such that a student could practically begin development of a quality system.
International and national quality system. Copyright, patent right, licenses, registration of software copyright, national standards and regulations, standardization and other organizations. Terminology.What is software quality?Software development tasks and quality assurance. Standards.Project planning. Standards.Requirements analysis. Standards.System design. Standards.Detailed design and programming. Standards.Testing. Standards.Configuration management. Standards.Quality assurance and new technologies.Quality assurance and human-computer interface.Software metrics.Process modeling and process evaluation.
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Standards and procedures. Security, safety, reliability. Security standards.ISO 9001 and CMM.
Requirements to pass the course
Exam grade in 10-points system could be obtained as follows: written in-auditorium work, 1.5 hours (any supporting materials allowed;
consultancy to colleagues forbidden) - 1 point submit example of operational concept description - 1 point submit example of requirements specification - 1 point submit example of design description - 1 point submit example of minimal set of test documentation - 1 point submit example of user documentation - 1 point submit example of verification and validation plan - 1 point submit example of configuration management plan - 1 point submit translation of IEEE standard (5 pp.) into Latvian - 1 point additional point could be earned if submitted examples are documents from real
project as well as for other outstanding contribution.
Course books
1. Darrel Ince. Software Quality Assurance - A Student Introduction._ McGraw-Hill, 1995, 243 p.
2. IEEE Standards Collection "Software Engineering", 1993 Edition._Institute of Electrical and Electronics Engineers, Inc.
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System Design
Author docent Jānis Bičevskis, Dr.sc.comp.Volume 4 credits,64 hoursSemester Testing form examinationPrerequisites noneCourse group
Abstract
Course aims at repeating and enhancing the knowledge from undergraduate studies about system design, to classify various methods of system analysis and design, and to deepen practical experience about system analysis and design as particular projects are implemented and analyzed.
Contents
Within the course the first topic is system analysis containing traditional approaches: requirements analysis, structured analysis, object oriented analysis; and also the newest and practically used methods of analysis. In the second part of the course via the analysis of concrete projects, system design is taught as direct continuation of system analysis.
1. Requirements analysis 1.1 Requirements gathering 1.2 Principles of requirements analysis 1.3 Prototyping 1.4 Specification
2. Structured analysis and its extensions2.1 Data flow diagrams 2.2 Extensions of data flow diagrams 2.3 Modeling of system functioning 2.4 ER-models
3. Object oriented analysis and data modeling3.1 Object oriented concepts3.2 Object oriented analysis modeling 3.3 Data modeling
4. Alternative analysis techniques and formal methods
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4.1 ORACLE DESIGNER 2000, method, features un implementation
4.2 GRADE, method, features un implementation4.3 RATIONAL ROSE, method, features un implementation4.4 ISTechnology method, features un implementation
5. System design 5.1 System design fundamentals5.2 Data flow oriented design 5.3 Object oriented design5.4 User interface design5.5 Real time design
Requirements for credit
During the course, one of the methods of system analysis and design should be acquired to the level of practical use, other ones should be learned up to the understanding of basic ideas, until students are able to fully learn them on their own. To pass the exam one should: 1. Prepare 45 minute presentation about one method of system
analysis and design. In the presentation the general idea of the method should be presented along with its applications, formal syntax, semantics and the tools supporting the method.
2. Analyze and give a report about some system project which is or could be implemented . The report should reflect the method and means used in the project, and lessons obtained through their use.
Literature
1. Roger S.Pressman. Software Engineering. A Practioner’s Approach. McGraw-Hill. Inc., 1992. pp. 775.
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UML and its Applications
Author docent Audris Kalniņš, Dr. hab. sc.comp.Volume 2 credits, 32 hoursSemester Testing form examinationPrerequisites course “Object -Oriented Analysis and Modeling”Course group
Abstract
One of the objectives is to teach those elements of the Unified Modeling Language (UML), which are not included in the traditional object-oriented modeling techniques (OMT). The main emphasis is on the use of UML for system analysis and design, with investigation of several typical case-studies as a basis
Content
1. UML and its role in system analysis and design2. Additional elements of UML (Use Case diagram, Sequence diagram, Collaboration
diagram)3. Use of UML for system analysis and design (investigation of typical case studies)4. Class diagram as a specification for object-oriented programs
Requirements
Students have to present in a seminar parts of the considered case studies, and have to build their own small examples
Literature
1. Terry Quatrani. Visual Modeling with Rational Rose and UML, Addison- Wesley,1997
2. Craig Larman. Applying UML and patterns: An Introduction to Object-Oriented Analysis and Design, Prentice Hall, 1997.
3. Hans-Erik Eriksson, Magnus Penker. UML Toolkit, J.Wiley, 1997
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Curriculumof Doctoral
studentsin Computer Science
Curricula Vitaeof the Teaching Staff
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CURRICULUM VITAE Andrejs Auziņš
Name - Andrejs Auziņš
Date and place or birth: 1959, Rīga, Latvia
Job title - Institute of Mathematics and Computer Scienceof University of Latvia leading researcher
Education
1977-1982 University of Latvia, Faculty of Physics and mathematics
1982-1985 University of Latvia, postgraduate student
Scientific degrees:
1988 Candidate of sciences of physics and mathematics
1993 Dr. dat. (Computer science)
Language - Latvian , English, Russian
Employment history-
1985-1988 Institute of Mathematics and Computer Scienceof University of Latvia researcher
1989-1992 Institute of Mathematics and Computer Scienceof University of Latvia , senior researcher
since 1993 Institute of Mathematics and Computer Scienceof University of Latvia, leading researcher
Training experience
Since 1992 I have taught Compilers course at the undergraguate and graduate level in University of Latvia. In 1996 I taught SQL course for several emploies groups of Telekom and Intorduction to Relational Data Model course for emploies group of The Central Statitical Burau of Latvia.
In 1997 I started taught ORACLE basics course at the graduate level in University of Latvia.
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CURRICULUM VITAE Jānis Āboltiņš
Name: Jānis Āboltiņš.
Date of birth: February 19th, 1943
Nationality: Latvian
Languages: Latvian (mother tongue)Russian (fluent)German (good)English (basic knowledge)
Education and professional training
1966 Dip. Eng., Latvian University of Agriculture, Jelgava
1986 Dr.hab.Ec., Latvian University, Riga
Professional Experience:
1991 to present Chairman of the Board Zenico Ltd, Riga
Duties include(1) formation and realisation of company’s strategy; (2) personnel management and company’s finance control; (3) consulting of entrepreneurs in questions of business development and management; (4) contacts with local enterprises’ managers and government officials
1989 - 1991 Minister, Ministry of Economics, Riga
Latvian national economy policy and regulation
1988 - 1989 Vice Chairman, Latvia State Planning Committee
Working out and managing of social policy programmes
1986 - 1988 Director of Finance, Agro-firm “Ādaži”, Ādaži
Financial strategy and controlling
1983 - 1986 Head of Department, Institute of National Economy, Riga
Research work in improving of national economy managing
1977 - 1983 Chairman, Riga City District Executive Committee
Planning and managing of communal services activities
1967 - 1977 Work in furniture enterprise, social organizations.
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CURRICULUM VITAE Jānis Bārzdiņš
Name: Jānis BārzdiņšDate and place of birth: 1937, Latvia
Education:
1954-1959 Undergraduate studies, Latvia State University, Faculty of Physics and Mathematics, Mathematics
1962-1965 Graduate studies, Latvia State University
Scientific degrees:
1965 Candidate of Science (Mathematics).
1976 Doctor of Science (Mathematics).
1985 Professor in Mathematical Cybernetics
1992 Dr. habil. Sc. Comp. by nostrification procedure.
Employment:
1959-1962 Assistant, Faculty of Physics and Mathematics, Latvia State University
1965-1971 Senior Scientific Associate, Computer Center, Latvia State University
Since 1971 Head of Software R&D Laboratory, Institute of Mathematics and Computer Science, University of Latvia
Since 1985 Professor, Faculty of Physics and Mathematics, University of Latvia
Other activities (currently):
True Member of the Academy of Sciences of Latvia (since 1992),
Member of the Latvian Council of Science,
Head of Computer Science Expert Commission of the Latvian Council of Science,
Director of Computer Science Master Program, University of Latvia
Research and Development:
Principal investigator in a series of R&D projects, concerning inductive synthesis, test case generation, specification languages and CASE tools for telecommunications and information systems.
Courses Taught:
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1966 - 1992 Theory of computation1985 Mathematical logic1992 Fundamentals of specification languagesSince 1992 Formal specifications ISince 1993 Formal specifications IISince 1993 Object-oriented modeling
List of Main Publications:
Books:
1. Trakhtenbrot B.A. and Barzdin J.M. Finite automata: behaviour and synthesis. - North-Holland, 1973, 321 p.
2. Auguston M.I., Balodis R.P., Barzdin J.M. et al. Programming in PL/1 OS/360, 1st ed. M., Finances and Statistics publishers, 1978; 2-nd ed. M., Finances and Statistics publishers, 1984, 327p. (in Russian).
3. Barzdin J.M., Kalnins A.A., Strods J.F. and Sitko V.A. Specification language SDL/PLUS and its applications. - Computing Center of Latvia State University, 1988, 312p. (in Russian).
Papers:
1. Barzdin J.M. Universal pulsing elements. Soviet Math. Dokl. 9: 523-525, 1964
2. Barzdin J.M. Universality problems in the theory of growing automata. -Soviet Math. Dokl. 9: 535-537, 1964
3. Barzdin J.M. The complexity of symmetry recognition by Turing machines. Problemi Kibernetiki, v.15, 1965 (in Russian)
4. Barzdin J.M. Capacity of the medium and behaviour of automata, - Soviet Math. Dokl. 10: 8-11, 1966
5. Barzdin J.M. Simulation of Boolean circuits by cellular automata. Problemi Kibernetiki, v.16, 1966 (in Russian)
6. Kolmogorov A.N. and Barzdin J.M. Implementation of networks in 3-dimensional space. Problemy Kibernetiki, v.19, 1967 (in Russian)
7. Barzdin J.M. Complexity of programs to determine whether natural numbers not greater than n belong to recursively enumerable set. Soviet Math. Dokl., 9: 1251 - 1254, 1968
8. Barzdin J.M. On computability by probabilistic machines. Soviet Math. Dokl., 10: 1464-1467, 1969
9. Barzdin J.M. On reconstruction of automata. - Problemi Kibernetiki, v. 21, 1969 (in Russian)
10. Barzdin J.M. On reconstruction of finite automata without information about the number of states. - DAN SSSR, v. 190, No. 5, 1970 (in Russian)
11. Barzdin J.M. On the relative frequency of solution of algorithmically unsolvable mass problems. - Soviet Math. Dokl., 11: 459-462, 1970
12. Barzdin J.M. Complexity of initial fragments of recursive enumerable sets. - DAN SSSR, v. 199, No. 2, 1971 (in Russian)
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13. Barzdin J.M. Prognostication of automata and functions, Proc. IFIP Congress 1971, North-Holland, pp.81-84, 1972
14. Barzdin J.M. and Freivalds R.V. On the prediction of general recursive functions. - Soviet Math. Dokl., 13: 1251-1254, 1972
15. Barzdin J.M. and Kalninsh J.J. On a language for the transformation of graphs intended for the specification of automata. - Automat. i Vychisl. Tekhn. 7(5):22-28, 1973
16. Barzdin J.M. and Kalninsh J.J. A universal automation with variable structure. - Automat. i Vychisl. Tekhn. 8(2): 10-17, 1973
17. Barzdin J.M., On the frequency solution of recursive enumerable sets. - Trudi Matem. Instituta im. Steklova, AN SSSR, CXXXIII, 1973 (in Russian)
18. Barzdin J.M., Agafonov V.N. The sets related to probabilistic machines. - Zeitschr. f. Math. Logig und Grundlagen d. Math., Bd. 20, 1974 (in Russian)
19. Barzdin J.M. Two theorems on limiting synthesis of functions. Theory of algorithms and programs, N1: 82-88, University of Latvia, 1974 (in Russian)
20. Barzdins J., Bicevskis J., Kalnins A. Construction of complete sample system for correctness testing.- Lc. Notes in Comp. Sc., v. 32, 1975 (in Russian)
21. Barzdin J.M. Inductive inference of automata, functions and programs. - Proc. of the 20-th International Congress of Mathematicians. Canada, 1974, v.2, p.455-560 ( Amer. Math. Soc. Transl. (2) 1977, v.109, pp.107- 112)
22. Barzdin J.M., Bicevskis J.J. and Kalnins A.A. Automatic construction of complete sample systems for program testing. - Proc. IFIP Congress 1977, North-Holland, 1977, pp.57-62
23. Barzdin J.M. The problem of reachability and verification of programs. - Lc. Notes in Comp. Sc., v.74, Springer Verlag, 1979
24. Barzdin J.M. On inductive synthesis of programs. - Lc. Notes in Comp. Sc., v.122, Springer Verlag, 1981
25. Barzdin J.M., Zarins A.K., Kalnins A.A. On a specification language.- Kibernetika, No. 6, 1982 (in Russian)
26. Barzdin J.M. Some rules of inductive inference and their use for program synthesis. - Proc. IFIP Congress 1983 (9-th World Computer Congress), North-Holland, 1983, pp.333-338
27. Barzdin J.M., Auguston M.J., Kalnins A.A. Specification language and program testing. - Tehnika sredstv svyazi: Sistemi svyazi, v. 3, 1984 (in Russian)
28. Barzdin J.M., Brazma A.M., Kinber J.B. Inductive inference: state-of-the-art, problems and future. - Kibernetika, No. 6, 1987 (in Russian)
29. Barzdin J.M. Algorithmic information theory. In Encyclopaedia of Mathematics, volume 1, pages 140 -142. D.Reidel (Kluwer Academic Publishers), 1988. Updated and annotated translation of the Soviet Mathematical Encyclopaedia
30. Barzdin J.M., Kalnins A.A. and Auguston M.I. SDL tools for rapid prototyping and testing. - In: SDL'89: The Language at Work, North- Holland, 1989, pp.127-134
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31. Barzdin J.M. Specification language SDL: state-of-the-art and problems. - Tehnika sredstv svyazi, No. 3, 1989 (in Russian)
32. Barzdin J., Brazma A. and Kinber J. Models of inductive syntactical synthesis. - Machine intelligence, 12, 1991, pp.139-148
33. Barzdins J. Editor Foreword. - Baltic Computer Science (Eds. J.Barzdins and D.Bjorner), Lc. Notes in Comp. Sc., v.502, Springer Verlag, 1991
34. Auzins A., Barzdins J., Bicevskis J. et al. Automatic construction of test sets. - Lc. Notes in Comp. Sc., v. 502, Springer Verlag, 1991, pp.287-360
35. Freivalds R., Barzdins J. and Podnieks K. Inductive inference of recursive functions. - Lc. Notes in Comp. Sc., v.502, Springer Verlag, 1991, pp.111-155
36. Barzdins J.M. and Barzdins G.J. Rapid construction of algebraic axioms from samples. - Theoretical Computer Science, 90, 1991, pp.199-208
36a Barzdins J.M. and Barzdins G.J. Rapid construction of algebraic axioms from samples. - In: Images of programming, North-Holland, 1991, pp.199- 208
37. Barzdins J.M. and Barzdins G.J. Towards efficient inductive synthesis: Rapid construction of local regularities. - Lc. Notes in Comp. Sc., v.659, Springer Verlag, 1993, pp.132-140
38. Barzdins J., Barzdins G., Apsitis K. and Sarkans U. Towards efficient inductive synthesis of expressions from Input/Output examples. - Lc. Notes in Comp.Sc., v. 744, Springer Verlag, 1993, pp.59-72
39. Barzdins J., Kalnins A, Podnieks K. et. al. GRADE Windows: an integrated CASE tool for information system development. - Proc. 6-th International Conference on Software Engineering and Knowledge Engineering, 1994, pp. 54-61
40. Barzdins J. Towards efficient inductive synthesis from Input/Output examples.-. Lc. Notes in Comp. Sc., v. 872, Springer Verlag, 1994
41. Barzdins J., Barzdins G. and Kalnins A. Rule - based approach to business modeling. Proc. 7-th International Conference on Software Engineering and Knowledge Engineering, 1995, pp. 161-165
42. Bārzdiņš J., Etmane I., Kalniņš A. and Podnieks K. - Towards Integrated Computer Aided Systems and Software Engineering Tool. - Proc. of the Second International Workshop on Advances in Databases and Information Systems, Moscow 1995, Phasis, pp. 10-14
43. Bārzdiņš J., Tenteris J., Viļums Ē.. Business Modeling Language GRAPES/BM (Version 3.0) and its Application. - Riga Information Technology Institute, Riga 1996, 112 p.
44. Kalnins A., Barzdins J. et al. - Business Modeling Language GRAPES-BM and Related CASE Tools. Proc. Second International Baltic Workshop on Databases and Information Systems, Tallinn, 1996, v.2, pp.3-16
45. Bārzdiņš J., Etmane I., Kalniņš A. and Podnieks K. - Towards Integrated Computer Aided Systems and Software Engineering Tools for Information Systems Design. - Advances in Databases and Information Systems, Springer Verlag, 1996, pp.3-11
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46. Bārzdiņš J. Freivalds R. and Smith C., Learning with Confidence.- Lc. Notes in Comp. Sc., v.1046, Springer Verlag, 1996, pp.207-218
47. Barzdins J. and Sarkans U., Incorporating Hypothetical Knowledge into the Process of Inductive Inference. - Lc. Notes in Comp. Sc., v. 1160, Springer Verlag, 1996, pp. 156-168
48. Kalnins A., Barzdins J. and Kalis A., GRADE-BM: Modeling and Simulation Facilities, Proc. of NWPER'96, Aalborg University, 1996, pp.71-86
49. Bārzdiņš J., Freivalds R. and Smith C., Learning Formulae from Elementary Facts. - Lc. Notes in Comp. Sc., v. 1208, Springer Verlag, 1997, pp. 272-285
50. Bārzdiņš J. and Kalniņš A. Enterprise Modeling and Business Process Reengineering: Tool Support. - Proc. International Conference and Exhibition “Information Technologies and Telecommunications in the Baltic States”, Riga, 1997, pp.69-73
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CURRICULUM VITAEGuntis Bārzdiņš
Name Guntis Bārzdiņš Date of Birth December 23, 1962 Address Institute of Mathematics and Computer Science, University of Latvia
Rainis blvd. 29Riga LV-1459, Latvia
Phone +371 7 212427, +371 9 206 943 (mob) Fax +371 7 820 153 E-mail [email protected]
Education
Ph.D. Siberian Division of USSR Academy of Sciences, (Novosibirsk, Russia), 1990, University of Latvia (Riga), 1992.
B.Sc. University of Latvia (Riga, Latvia), 1986
Work Experience
1992-present Senior Researcher, LATNET Technical director, Lecturer, Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia
1991-1992 Postdoctoral Research Associate, Department of Computer Science, New Mexico State University, Las Cruces, NM, USA
1985-1991 Junior Researcher, Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia
Professional activities
Advisor for Baltic countries in ACM Committee on Central and Eastern Europe (CECE)
Member of the Latvian Academic Networking board
Member of Internet Society
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List of Publications
1. Barzdins, G.J. Eksperimenti so smeshannimi vichislenijami (Experiments with mixed computation), Programmirovanie, 1:30-43, 1987. (in Russian)
2. Barzdins G.J., Krastins P.J., Linabergs L.J., Principi realizacii jazikov specifikacii SDL i FOPS (Principles of implementation of the SDL and FOPS specification languages), Avtomatika i Vychislitelnaja Tekhnika, 21(5):22-28, 1987. (in Russian)
3. Barzdins G., Mixed Computation and Compiler Basis, Proc. of Workshop on Partial and Mixed Computation, Denmark, October 1987, (Eds. D.Bjorner, A.P.Ershov, N.D.Jones), North-Holland, p.15-26, 1988.
4. Barzdins G.J.,Bulyonkov M.A., Smeshannie vichislenija i transljacija: linearizacija i dekompozicija transljatora (Mixed computation and translation: linearization and decomposition of compiler, Preprint 791, VC SO AN SSSR, Novosibirsk, 32p., 1988. (in Russian)
5. Barzdins G.J., Bulyonkov M.A., Smesannie vichislenia kak sredstvo videlenija faz transljacii (Mixed computation as a mean for separating compilation phases), Metodi transljacii i konstruirovanija programm (Methods for compilation and assembling of programs), Ed. Ershov A.P., Novosibirsk, p.21-23, 1988. (in Russian)
6. Barzdins G.J., Smesannie vichislenija pri realizacii abstraktnih tipov dannih na Prologe (Mixed computation for implementation of ADT in Prolog), Metodi transljacii i konstruirovanija programm (Methods for compilation and assembling of programs), Ed. Ershov A.P., Novosibirsk, p.18-20, 1988. (in Russian)
7. Barzdins G., Inductive synthesis of encoding for algebraic data types, Lecture Notes in Computer Science, Springer Verlag, 397:328-338, 1989.
8. Barzdin, G.J. and Bulyonkov, M.A. Chastichnie vichislenija i dekompozicija programm ("Partial Computation and Program Decomposition), Programmirovanie, 1:50-61, 1990. (in Russian)
9. Barzdins G.J., Sistema induktivnogo sinteza sistem podstanovok termov (System for inductive synthesis of term rewriting systems), University of Latvia, Riga, 42p., 1990. (in Russian)
10. Barzdins G., Inductive Synthesis of Term Rewriting Systems, Lecture Notes in Computer Science, Springer Verlag, 502:253-285, 1991.
11. Barzdins J., Barzdins G., Rapid construction of algebraic axioms from samples, Theoretical Computer Science, 90:199-208, 1991.
12. Barzdins J, Barzdins G., Towards Efficient Inductive Synthesis: Rapid Construction of Local Regularities, Lecture Notes in Computer Science, Springer Verlag, 659:132-140, 1993.
13. Barzdins J., Barzdins G., Apsitis K., Sarkans U., Towards Efficient Inductive Synthesis of Expressions from Input/Output Examples, Eds. Meldal S., Haveraaen M., Report 78, University of Bergen, Bergen, p.75-85, 1993.
14. Barzdins J., Barzdins G., Apsitis K., Sarkans U., Towards Efficient Inductive Synthesis of Expressions from Input/Output Examples, Lecture Notes in Computer Science, Springer Verlag, 744:59-72, 1993.
15. G.Barzdins. Research Networks in the Baltic countries, Proceeding NORDUNET-94, May31-June2, Umea, 1994.
16. Barzdins J., Kalnins A., Barzdins G., Rule-based Approach to Business Modelling, Proceedings of the SEKE’95, Knowledge Systems Institute, 1995.
17. G.Bārzdiņš, I.Murane, Internet in Latvia, BALTIC IT REVIEW, Nr.1, 1996
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18. G.Barzdins, J.Kikuts, R.Balodis, "Internet Development Trends in Latvia", Baltic IT&T 97, April 2-4, 1997, Riga.
19. G.Barzdins, "Baltic Network Proliferation", NORDUnet'97 Conference, Reykjavik, June 29 - July 1, 1997.
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Curriculum vitaeAlvis Brāzma
Name Alvis Brazma ,
Born: 1959
Education:
M.Sc. in Mathematics from University of Latvia (1982);
Ph.D. in Computer Science from Moscow State University (1988).
Employment
Currently Leading researcher at the Institute of Mathematics and Computer Science and an associate professor at faculty of Mathematics and Physics at the University of Latvia. Has worked in New Mexico State University (1991-1992) and in University of Helsinki (1995-1996) and in the European Bioinformatics Institute (1997). More than 20 publications on automatic program synthesis, grammar inference, string algorithms, graph drawing and computational biology in internationally recognized journals and scientific editions. Current scientific interests is computational biology and data mining.
List of most important publications
1. A. Brazma, J. Vilo, E. Ukkonen, K. Valtonen. Data mining for regulatory elements in yeast genome. In Proc. of 5th International Conference Intelligent Systems for Molecular Biology ISMB'97, AAAI Press, 1997, p.65-74.
2. A. Brazma, K. Cerans. Noise-tolerant inductive synthesis of regular expressions from good examples. New Generation Computing, Vol. 15, Januray 1997, p. 105-140.
3. A. Brazma. Efficient learning of regular expressions from approximate examples. In Computational Learning Theory and Natural Learning Systems, Vol 4, MIT Press, 1997, p.351--366.
4. A. Brazma, E. Ukkonen, J. Vilo. Discovering unbounded unions of regular pattern languages from positive examples. In Proc. of the 7th Annual International Symposium on Algorithms and Computation (ISAAC-96), Lect. Notes in Coputer Science, vol. 1178, 1996, p.95-104.
5. A. Brazma, I. Jonassen, E. Ukkonen, J. Vilo. Discovering patterns and subfamilies in biosequences, In Proc. of 4th International Conference Intelligent Systems for Molecular Biology ISMB'96, AAAI Press, 1996, p.34-43.
6. A. Brazma. Efficient identification of regular expressions from representative examples. In Proc. of the 6th Annual Workshop on Computational Learning Theory COLT'93, ACM press, 1993, p.236-242.
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7. A. Brazma. Inductive synthesis of dot expressions. Lect. Notes in Computer Science, Vol 502, Springer, 1991, p.156-212.
8. J. Barzdin, A. Brazma, J. Kinber. Models of inductive syntactical synthesis. Machine Intelligence, Vol 12, Oxford University Press, 1990, p.139-148.
9. A. Brazma, J. Kinber. Generalized regular expressions - a language for synthesis of programs with branching in loops. Theoretical Computer Science, 46, 1986, p.175-195, North Holland.
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Curriculum VitaeJānis Cīrulis
Name Jānis CīrulisYear and place of birth: 1943, LatviaCitizenship: Latvia Identity No. 110443--11497Title and affiliation: Associate Professor at the Faculty of Physics and Mathematics,
University of Latvia {Latvian State University in period 1945--1990.} (since 1989)
Education: Latvian State University (grad. 1965) Professional certification: in Mathematics and Computer Science
Earned degrees Cand. Sci. Phys.& Math., get from Leningrad State University (1988),
Dr. Math., get from University of Latvia (1992)
Research area:
Mathematical Logic and Universal Algebra, with applications to Computer Science
Career history:
junior research worker at the Semiconductor laboratory of Latvian State University (1965--1971),
senior lecturer at the Faculty of Physics and Mathematics of Latvian State University (1971--1989)
Professional memberships: American Mathematical Society (since 1989),
Latvian Mathematical Society (since 1993)
Other professional activities:
reviewer for Mathematical Reviews (since 1987) and for Zentralblatt für Mathematik (since 1980),
leader of a research group (since 1993)
Training and methodical publications:
1. Lekcii po matematicheski logike i teorii mnozhestv, I, II. LGU, Riga, 1975.
2. Matemātiska loìika nematemātiíiem, 1. puse. LVU, Rīga, 1978. (ar līdzaut.)
3. Metodiski norādījumi par LVU 1982. g. iestājeksāmeniem matemātikā. LVU, Rīga, 1983. (ar līdzaut.)
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4. 1983.g. iestājeksāmeniem matemātikā. Metodiski norād jumi. LVU, Rīga, 1984. (ar līdzaut.) LVU 1989. g. iestājeksāmeni matemātikā. Metodiski norādījumi. LU, Rīga, 1990.
Other publications:
in scientific journals 52,
conference abstracts 21,
programs of lecture courses 10,
rewievs (in abstract and review journals 165
Courses taught:
Discrete Mathematics, Linear Algebra, Mathematical Logic, Number Systems, various undergraduate and graduate courses on applications of algebra and mathematical logic in computer science
Jan. 16, 1998
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Curriculum VitaeKārlis Čerāns
Name Kārlis Čerāns
Born: 1965
Education: 1983 - 1988 Latvian State University, Faculty of Physics and Mathematics, student
1988 - 1991 University of Latvia, Institute of Mathematics and Computer Science, doctoral student
09.1992 - 08.1993, 03.1994 - 06.1994, post-graduate student at University of Goeteborg and Chalmers University of Technology (Goeteborg, Swveden)
Scientific degree: 1992, Dr.sc.comp.
Employment: 1985 - 1988 IMCS UL, technical staff,
1988 - 1993 IMCS UL, junior researcher,
1993 IMCS UL, researcher,
since 1994 IMCS UL, senior researcher,
1994 - 1995 Faculty of Physics and Mathematics, teacher,
since 1995 Faculty of Physics and Mathematics, docent,since 1995 Member of Latvian Parliament (Saeima).
Papers:
In scientific journals and proceedings: 19
Other scientific papers: 3
Methodic materials: 6
Research directions:
Specification and verification of real-time systems, algorithmic problems in analysis of extended automata, inductive synthesis of programs.
Academic courses:
1991 Theory of Parallel Processes
since 1993 Program Verification
since 1993 Foundations of Specification Languages
1993 - 1996 Combinatorial Algorithms
1994 - 1996 Foundations of Computer Science
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March 1, 1998
Kārlis Čerāns
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Curriculum VitaeRūsiņš Mārtiņš Freivalds
Name: Rūsiņš Mārtiņš Freivalds
Born: 1942
Scientific degrees:
Dr. habil. math. - by nostrification procedure in 1992 from Latvian Council of Science
Doctor of Science ( Mathematics ) - in 1985 from Moscow State University
Candidate of Science ( Mathematics ) - in 1971 from the Institute of Mathematics, Academy of Science of USSR, Novosibirsk (thesis advisor Prof. Dr. B.A.Trakhtenbrot
graduated from the Latvian State University, Riga, Latvia in 1965 (mathematics, advisor Prof.Dr. B.A.Trakhtenbrot )
Employment:
1992- Professor, Head of Division of Discrete Mathematics, University of Latvia
1990 - 1991 Professor, Chief Scientific Associate in Institute of Mathematics and Computer Science, University of Latvia
1985 - 1990 Professor, Deputy Director of Computing Center, Latvian State University
1975 - 1985 Head of Laboratory, Computing Center, Latvian State University
1971 - 1975 Senior Scientific Associate, Computing Center, Latvian State University
1965 - 1966 Assistant, Faculty of Physics and Mathematics, Latvian State University
Member of the Latvian Academy of Science (1992)
Member of the European Association of Theoretical Computer Science (1979)
Visiting positions
1996 Mälardalens University, Eskilstuna, Sweden1994 University of Bonn, Germany1994 National University of Singapore1993 Electrotechnical Laboratory, Tsukuba, Japan1991 Humboldt University, Berlin, Germany1980 Kalinin State University, Kalinin, USSR
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Scientific publications (numbers):
Monographs 1Papers in ISC scientific journals 63Papers in other scientific journals and in collections of papers 64Patents 0Dictionaries 0Conference abstracts 29
Pedagogical publications (numbers):
Textbooks 0Other texts for students and teachers 10Methodological papers 10
Other publications (numbers):
Popular scientific papers 18
Research:
The primary area of my research has always been complexity of computation. In 1975 I have proven the very first theorem on advantages of randomized algorithms over deterministic ones. Namely, I have proven that randomized Turing machines can use less running time than deterministic ones to compute certain functions. Recently I have developed new powerful methods to prove lower bounds for time and space complexity of randomized algorithms.
I have published various results in Inductive Inference. I have tried to use deep methods of the classical mathematics for problems in Theoretical Computer Science. I would like to mention the usage of constructive ordinals to measure the complexity of Inductive Inference, and the usage of Group Theory in Inductive Inference.
Invited Lectures:
22nd International Colloquium "Automata, Languages and Programming" (Szeged, Hungary, 1995)
3rd Annual Workshop on Computational Learning Theory ( Rochester, USA, 1990 )Symposium on Algorithms ( Tokyo, Japan, 1990 )Symposia on Mathematical Foundations of Computer Science ( High Tatras,
Czechoslovakia, 1986; High Tatras, Czechoslovakia, 1981; Jadvisin,Poland, 1974 )
Symposia on Fundamentals of Computer Science ( Linkoping, Sweden, 1983; Kazan, USSR, 1988)
USSR conferences on Mathematical Cybernetics ( Saratov, 1985; Irkutsk, 1987USSR conferences on Mathematical Logics (Kishinew, 1978)
Program Committees:
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13th World Computer Congress (Hamburg, Germany, 1994)International Symposium on Theoretical Aspects of Computer Science (Lübeck,
Germany, 1997)International Colloquia "Automata, Languages and Programming" (Paderborn,
Germany, 1996; Lund, Sweden, 1993)International Workshop "Algorithmic Learning Theory" (Tokyo, Japan,1993)Workshop "Computational Learning Theory" (Santa Barbara, USA, 1992)Second European Conference "Computational Learning Theory" (Barcelona, Spain,
1995)International Symposia "Mathematical Foundations of Computer Science" (Prague,
Czechoslovakia, 1992; Rytro, Poland, 1989; Bratislava, Slovakia, 1997)Scandinavian Workshop on Algorithm Theory (Stockholm, Sweden, 1998)
Chair of Program Committee:
Workshop "Randomized Algorithms" (Brno, Czech Republic, 1998)
Talks:
Tokyo Institute of Technology, Japan (1993)University of Osaka,Japan (1993)Electrotechnical Laboratory, Tsukuba, Japan (1990, 1993)Hitachi Research center, Japan (1990, 1993) Fujitsu Research Center, Japan (1990, 1993)NEC Research Center, Japan (1993)Cornell University, USA (1990, 1994)University of California in Berkeley, USA (1993)University of Washington in Seattle, USA (1993)Duke University, USA (1994)University of Pittsburgh, USA (1994)University of Maryland, USA (1990, 1993, 1995)University of Boston, USA (1995)Rochester University, USA (1990)New Mexico State University, USA (1993) University of Delaware, USA (1995)University of Montreal, Canada (1993)University of Bonn, Germany (1993, 1994) Humboldt University, Berlin, Germany (1980, 1988)Technical University of Berlin, Germany (1991)Technical University of Munich, Germany (1991)University of Kaiserslautern, Germany (1997)University of Paderborn, Germany (1996)University of Greifswald, Germany (1980, 1997)Friedrich-Schiller University, Jena, Germany (1980, 1997)Hebrew University, Jerusalem, Israel (1990)Tel Aviv University, Israel (1990)Royal Technical University, Stockholm, Sweden (1996)Lund University, Sweden (1993, 1995)M\" alardalens University, Eskilstuna, Sweden (1996)
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Link\" oping University, Sweden (1996)University of Turku, Finland (1976,1988,1992)University of Helsinki, Finland (1976,1988)University of Oulu, Finland (1976)Auckland University, New Zealand (1996)Charles University, Prague, Czech Republic (1972,1984,1988)University of Brno, Czech Republic (1972)Warsaw University, Poland (1974, 1985)Cracow University, Poland (1974)University of Lublin, Poland (1974)Bucharest University, Romania (1990)Moscow State University, Russia (1970, 1981, 1984)Novosibirsk State University, Russia (1970, 1984)Kazan State University, Russia (1978, 1985)Tallinn Technical University, Estonia (1979)Riga Technical University, Latvia (1981) Liepāja Pedagogical University, Latvia (1982)
Courses of lectures for students:
1972 - Complexity of algorithms1974-1975 Linear algebra1975-1976 Theory of numberings1992- Theory of algorithms1993- Main notions of mathematics1994- Data protection and cryptography1994- Algorithms. automata and formal languages, 11994- Algorithms. automata and formal languages, 2
Advising: Research direction
Doctoral Theses
1974 Efim Kinber1983 Agnis Andþāns1989 Māris Alberts1990 Daina Taimiòa1991 Jānis Kaòeps1994 Juris Vīksna1997 Andris Ambainis
Master Theses
1994 Kalvis Apsītis1995 Dace Gobleja1995 Gints Tervits
99
1996 Juris Smotrovs1996 Raimonds Simanovskis1996 Gatis Gurckis 1997 Andris Ambainis
Honorary titles and prizes:
1976 Latvia YCL prize for the work "Theory of Inductive Inference"
1986 Honorary scientist of Latvia SSR
Prizes of my students:
1972 Efim Kinber - a diploma in the Annual competition for the best student scientific paper of the USSR
1973 Agnis Andþāns - Prize of the Academy of Science of the Latvian SSR for the best student scientific paper
1975 Agnis Andþāns - Prize of the Academy of Science of the Latvian SSR for the best student scientific paper
1978 Lev Lisagor - Prize of the Academy of Science of the Latvian SSR for the best student scientific paper
1979 Vita Brçmere-Kāle - Prize of the Academy of Science of the Latvian SSR for the best student scientific paper
1992 Kalvis Apsītis - Charles Babbage Prize of the University of Latvia
1994 Andris Ambainis - Charles Babbage Prize of the University of Latvia
1995 Andris Ambainis - a special mentioning at the {\em Computing Research Association (U.S.A.)} Annual competition for the title of the best Computer Science undergraduate student
1996 Andris Ambainis - Charles Babbage Prize of the University of Latvia
1996 Andris Ambainis - Young Scientist Award from Academia Europeana
1996 Andris Ambainis - Award for the best Bachelor thesis from SWH Izglītībai, Zinātnei un Kultūrai
1996 Juris Smotrovs - Award for the best Master thesis from SWH Izglītībai, Zinātnei un Kultūrai
1997 Juris Smotrovs - Award from the International Federation for Information Processing (IFIP) for the best student paper at the 3rd
European Conference on Computational Learning Theory
1997 Atis Straujums - Charles Babbage Prize of the University of Latvia
Received grants:
1990-1993 Grant No. 90.619 Randomized methods in inductive inference from Latvia Council of Science
100
1994-1996 Grant No. 93.599 Mathematical principles of randomized algorithms in inductive inference from Latvia Council of Science
1997-1999 Grant No. 96.0282 Complexity of randomized algorithms from Latvia Council of Science
1992-1996 Grant No. 9119540 from the National Science Foundation for co-operative research in inductive inference for the University of Maryland and the University of Latvia
1995-1998 Grant No. 9119540 from the National Science Foundation for co-operative research in inductive inference for the University of Maryland and the University of Latvia
1994-1995 Grant from Academy of Sweden for a joint research in Computer Science for the University of Lund and the University of Latvia
1997-2000 Grant from Academy of Sweden for a joint research in Computer Science for the Mälardalens University and the University of Latvia
Activities:
1994-1996 Member of the Supervisory Council of the Latvian Academy of Science
1993 Member of the Senate of the University of Latvia
1995 Member of the Working Group WG 1.4 of the International Federation for the Information Processing (IFIP)
List of publications byRūsiņš Mārtiņš Freivalds
Scientific publications:
Monographs
1. R.Freivalds, D. Taimiņa, E.B. Kinber Fundamentals of Computers. Kiev, Radianska skola, 1986 (in Russian)
Papers in ISC scientific journals
1. R. Freivalds. Completeness criteria for partial Boolean and multi-valued functions. "Dokladi AN SSSR ", 1966, v. 167, No. 6, p. 1249-1250 (in Russian)
2. R. Freivalds. Completeness up to coding of systems of functions in multi-valued logics and the complexity of its recognition.} " Dokladi AN SSSR ", 1968, v. 180, No.4, p. 803-805 (in Russian)
3. R. Freivalds. Codings of finite sets and criteria of completeness up to a coding in 3-valued logics. " Dokladi AN SSSR ", 1970, v. 190, No. 5, p. 1034- 1037 (in Russian)
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4. J. Bārzdiņš, R. Freivalds. On prediction of general recursive functions " Dokladi AN SSSR ", 1972, v. 206, No. 3, p. 521-524 (in Russian)
5. R. Freivalds. On synthesis in the limit indices of total recursive functions in various computable numberings. " Dokladi AN SSSR ", 1974, v.219, No. 4, p. 812-814 (in Russian)
6. R. Freivalds. Functions computable in the limit by probabilistic Turing machines. " Lecture Notes in Computer Science ", Springer, 1975, v. 28, p. 77-87.
7. R. Freivalds. Minimal G\" odel numbers and their identification in the limit. "Lecture Notes in Computer Science", Springer, 1975, v. 32, p. 219-225.
8. R. Freivalds. On probabilistic recognition with isolated cut-point of sets nonrecognizable by deterministic machines. "Izvestija VUZ. Matematika", 1977, No. 1 (176), p. 100-107 (in Russian)
9. R. Freivalds, E. Ikaunieks. On some advantages of nondeterministic machines over probabilistic ones. " Izvestija VUZ. Matematika ", 1977, No. 2 (177), p. 118-123 (in Russian)
10. R. Freivalds. Effective operations and functionals computable in the limit. "Zeitschrift für Mathematische Logik und Grundlagen der Mathematik ", 1978, Bd.24, H. 3, S. 193-206 (in Russian)
11. R. Freivalds. Recognition of languages with high probability by various types of automata. "Dokladi AN SSSR", 1978, v. 239, No. 1, p. 60-62 (in Russian)
12. R. Freivalds. Recognition of languages by finite probabilistic multitape and multihead automata. " Problemi peredachi Informacii ", 1979, v. 15, No. 3, p. 99-106 (in Russian)
13. R. Freivalds. Recognition of languages by probabilistic real-time Turing machines and pushdown automata. " Problemi peredachi informacii ", 1979, v. 15, No. 4, p. 96-101 (in Russian)
14. R. Freivalds. Fast probabilistic computation schemes. "Kibernetika ", 1980, No.6, p. 150-151 (in Russian)
15. R. Freivalds. Two-way finite probabilistic automata and space-bounded Turing machines. "Dokladi AN SSSR", 1981, v. 256, No. 6, p. 1326-1329 (in Russian)
16. R. Freivalds. Capabilities of various models of one-way probabilistic automata. "Izvestija VUZ. Matematika", 1981, No. 5 (228), p. 26-34 (in Russian)
17. R. Freivalds, E.B.Kinber and R.Wiehagen. Inductive inference and computable one-one numberings. "Zeitschrift f\" ur Mathematische Logik und Grundlagen der Mathematik", 1982, Bd. 28, No. 5, S. 463-479
18. R. Freivalds. Fast probabilistic algorithms} "Lecture Notes in Computer Science", Springer, 1979, v. 74, p.57-69
19. R. Freivalds. Probabilistic two-way machines. " Lecture Notes in Computer Science", Springer, 1981, v. 118, p. 33-45
20. R. Freivalds. Projections of languages recognizable by probabilistic and alternating finite multitape automata. "Information Processing Letters", 1981, v. 13, No. 4/5, p. 195-198
102
21. R. Freivalds, E.B.Kinber and R.Wiehagen. On the power of probabilistic strategies in inductive inference. " Theoretical Computer Science ", 1984, v. 28, No. 1/2, p. 111-134
22. R. Freivalds, E.B.Kinber and R.Wiehagen. Connections between identifying functionals, standardizing operations and computable numberings. " Zeitschrift f\" ur Mathematische Logik und Grundlagen der Mathematik ", 1984, Bd. 30, No. 2, S. 145-164
23. R. Freivalds. Space and reversal complexity of probabilistic one-way Turing machines. " Lecture Notes in Computer Science ", Springer, 1983, v. 158, p. 159-170
24. R. Freivalds. Space and reversal complexity of probabilistic one-way Turing machines. " Annals of Discrete Mathematics ", 1985, v. 24, p. 39-50
25. R. Freivalds. Probabilistic and deterministic circuits consisting of Boolean gates and delays. " Izvestija VUZ. Matematika ", 1985, No. 7 (278), p. 40-44 (in Russian)
26. F. Ablaev and R. Freivalds. Why sometimes probabilistic algorithms can be more effective. "Lecture Notes in Computer Science ", Springer, 1986, v. 233, p. 1-14
27. R. Freivalds. On running time for probabilistic Turing machines without errors. " Teorija Verojatnostei i ee Primenenija ", 1987, v. 32, No. $ p. 565-567 (in Russian)
28. R. Freivalds, E.B.Kinber and R.Wiehagen. Probabilistic versus determinstic inductive inference in nonstandard numberings. " Zeitschrift f\" ur Mathematische Logik und Grundlagen der Mathematik ", 1988, Bd. 34, H. 6, S. 531-539
29. R. Freivalds, C.H.Smith and M. Velauthapillai. Trade-off among parameters affecting inductive inference. "Information and Computation ", 1989, v. 82, No. 3, p. 323-343
30. J.Kaòeps and R. Freivalds. Minimal nontrivial space complexity of probabilistic one-way Turing machines. " Lecture Notes in Computer Science ", Springer, 1990, v. 452, p. 355-361
31. R. Freivalds. Inductive inference of recursive functions: qualitative theory. "Lecture Notes in Computer Science", Springer, 1991, v. 502,p. 77-110
32. J. Bārzdiņš, R. Freivalds and K. Podnieks. Inductive inference of recursive functions: complexity bounds. "Lecture Notes in Computer Science", Springer, 1991, v. 502, p. 111-155
33. R. Freivalds. Complexity of probabilistic versus deterministic automata. "Lecture Notes in Computer Science", Springer, 1991, v. 502, p. 565-613
34. J. Kaòeps and R. Freivalds. Running time to recognize nonregular languages by 2-way probabilistic automata. "Lecture Notes in Computer Science", Springer, 1991, v. 510, p. 174-185
35. R. Freivalds and C.H.Smith. Memory limited inductive inference machines. "Lecture Notes in Computer Science", Springer, 1992, v. 621, p. 19-29
36. K.Apsītis, R. Freivalds, M.Kriíis, R.Simanovskis and J. Smotrovs. Unions of identifiable classes of total recursive functions. "Lecture Notes in Computer Science", Springer, 1992, v. 642, p. 99-107
103
37. R. Freivalds and A.G.Hoffmann. An inductive inference approach to classification. "Lecture Notes in Computer Science", Springer, 1992, v. 642, p. 187-196
38. R. Freivalds, E.B.Kinber and R.Wiehagen. On the power of inductive inference from good examples. "Theoretical Computer Science", 1993, v. 110, p.131-144
39. R. Freivalds and C.H.Smith. On the role of procrastination in machine learning. "Information and Computation", 1993, v.107, No.2, p.237-271
40. R. Freivalds and M.Karpinski. Lower space bounds for randomized computation. " Lecture Notes in Computer Science ", Springer, 1994,v.820,p.580-592
41. R. Freivalds, R.Wiehagen and O.Botuscharov. Identifying nearly minimal Goedel numbers from additional information. " Lecture Notes in Computer Science ", Springer, 1994, v.872, p.91-99
42. R. Freivalds, D.Gobleja, M.Karpinski and C.H.Smith. Co-learnability and FIN-identifiability of enumerable classes of total recursive functions. " Lecture Notes in Computer Science ", Springer, 1994, v.872, p.100-105
43. R. Freivalds, E.B.Kinber and C.H.Smith. On the intrinsic complexity of learning. " Lecture Notes in Computer Science ", Springer, 1995, v.904,p.154-168
44. R. Freivalds and S.Jain. Kolmogorov numberings and minimal identification. " Lecture Notes inComputer Science ", Springer, 1995, v.904, p. 182-195
45. R. Freivalds and M.Karpinski. Lower time bounds for randomized computation. " Lecture Notes in Computer Science ", Springer, 1995, v.944, p.183-195
46. L.Fortnow, R. Freivalds, W.I.Gasarch, M.Kummer, S.A.Kurtz, C.H.Smith and F.Stephan. Measure, category and learning theory. "Lecture Notes in Computer Science ", Springer, 1995, v.944, p.558-569
47. R. Freivalds, E.B.Kinber and R.Wiehagen. Error detecting in inductive inference. " Lecture Notes in Computer Science ", Springer, 1995, v.961,p.25-48
48. R. Freivalds, E.B.Kinber and R.Wiehagen. Learning from good examples. " Lecture Notes in Computer Science ", Springer, 1995, v.961, p.49-62
49. R. Freivalds, E.B.Kinber and C.H.Smith. Probabilistic versus deterministic memory limited learning. " Lecture Notes in Computer Science", Springer, 1995, v.961, p.155-161
50. R. Freivalds, E.B.Kinber and R.Wiehagen. How inductive inference strategies discover their errors. "Information and Computation", 1995,v.118, No 2, p.208-226
51. R. Freivalds, E.B.Kinber and C.H.Smith. On the intrinsic complexity of learning. "Information and Computation", 1995, v.123, No 1, p.64-71
52. R. Freivalds, E.B.Kinber and C.H.Smith. On the impact of forgetting on learning machines. "Journal of the ACM", 1995, v.42, No.6, p.1146-1168
53. J. Bārzdiņš, R. Freivalds and C.H.Smith. Learning with confidence. "Lecture Notes in Computer Science ", Springer, 1996, v.1046, p.207-218
54. A.Ambainis, R. Freivalds and C.H.Smith. General inductive inference types based on linearly-ordered sets. "Lecture Notes in Computer Science ", Springer, 1996, v.1046, p.243-256
104
55. K.Apsītis, R. Freivalds and C.H.Smith. On duality in learning and the selection of learning teams. "Information and Computation", 1996, v.129, No. 1, p.53-62
56. K.Apsītis, R. Freivalds, R.Simanovskis, and J.Smotrovs. Unions of identifiable families of languages. "Lecture Notes in Computer Science ", Springer, 1996, v.1147,p.48-58
57. A.Ambainis and R. Freivalds. Transformations that preserve learnability. " Lecture Notes in Computer Science ", Springer, 1996, v.1160, p.299-311
58. J. Bārzdiņš, R. Freivalds and C.H.Smith. Learning formulae from elementary facts. "Lecture Notes in Computer Science ", Springer, 1997, v.1208, p.272-285
59. R. Freivalds, G. Tervits, R. Wiehagen, and C.H.Smith. Learning small programs with additional information. "Lecture Notes in Computer Science ", Springer, 1997, v.1234, p.102-112
60. A.Ambainis, R. Freivalds, and M. Karpinski. Weak and strong recognition by 2-way randomized automata. "Lecture Notes in Computer Science ", Springer, 1997, v.1269, p.171-182
61. J. Kaòeps, D. Geidmanis, and R. Freivalds. Tally languages accepted by Monte Carlo pushdown automata. "Lecture Notes in Computer Science ", Springer, 1969, v.1234, p.183-192
62. A. Ambainis, K. Apsītis, R. Freivalds, W. Gasarch, C.H.Smith. Team learning as a game. "Lecture Notes in Computer Science ", Springer, 1997, v.1316, p.2-17
63. A. Ambainis, K. Apsītis, C. Calude, R. Freivalds, M. Karpinski, T. Larfeldt, I. Sala, and J. Smotrovs. Effects of Kolmogorov complexity present in inductive inference as well. "Lecture Notes in Computer Science ", Springer, 1997, v.1316, p.244-259
Other scientific papers
1. R. Freivalds. Complexity of palindromes recognition by Turing machines with an input. " Algebra i Logika ", 1965, v.4, No. 1, p. 47-58 (in Russian)
2. R. Freivalds. On the order of magnitude of complexity functions for Turing machines. " Algebra i Logika ", 1966, v. 5, No. 5, p. 85-94 (in Russian)
3. R. Freivalds. Functional completeness of partial Boolean functions. "Diskretnij Analiz ", 1966, No. 8, p. 55-68 (in Russian)
4. R. Freivalds. Functions and functionals computable in the limit. " Theory of Algorithms and Programs ", Riga, University of Latvia, 1974, v. 210, p. 6-19 (in Russian)
5. R. Freivalds and K.Podnieks. On computation in the limit by nondeterministic Turing machines. "Theory of Algorithms and Programs ", Riga, University of Latvia, v. 210, p. 25-31 (in Russian)
6. R. Freivalds. On computation in the limit by probabilistic Turing machines. " Theory of Algorithms and Programs", Riga, University of Latvia, v. 210, p. 32-47 (in Russian)
7. R. Freivalds. Uniform and nonuniform prediction. " Theory of Algorithms and Programs ", v. 210, p. 89-100 (in Russian)
105
8. J. Bārzdiņš and R. Freivalds. Prediction and synthesis in the limit for effectively enumerable classes of functions. " Theory of Algorithms and Programs ", Riga, University of Latvia, v. 210, p. 101-111 (in Russian)
9. R. Freivalds. Possibility to synthesize the indices of total recursive functions in various computable numberings. "Theory of Algorithms and Programs", Riga, University of Latvia, 1975, v.233, p. 3-25 (in Russian)
10. J. Bārzdiņš and R. Freivalds. Relations between predictability and synthesizability in the limit. "Theory of Algorithms and Programs ", Riga, University of Latvia, 1975, v. 233, p. 25-34 (in Russian)
11. R. Freivalds. On complexity and optimality of computation in the limit. "Theory of Algorithms and Programs", 1975, v. 233, p. 155-173 (in Russian)
12. R. Freivalds. Fast computations by probabilistic Turing machines. "Theory of Algorithmsand Programs", Riga, University of Latvia, 1975, v. 233, p.201-205 (in Russian)
13. R. Freivalds and E.B.Kinber. Identification in the limit of minimal Gödel numbers. " Theory of Algorithms and Programs ", Riga, University of Latvia, 1977, p. 3-34 (in Russian)
14. R. Freivalds. Probabilistic machines can use less running time. "Information Processing'77" (Proc. IFIP Congress'77), North Holland, 1977, p. 839-842
15. R. Freivalds. A fast probabilistic test of correctness for the multiplication of integers. "Avtomatika i Vychislitel'naja Tekhnika ", 1979, No. 1, p. 40-43 (in Russian)
16. R. Freivalds. Recognition of languages by finite multihead probabilistic and deterministic automata. "Avtomatika I Vychislitel'naja Tekhnika ", 1979, No.3, p. 15-20 (in Russian)
17. R. Freivalds. On running time of deterministic and nondeterministic Turing machines. "Latviiskij matematicheskij ezhegodnik ", Riga, Zinātne, 1979, v. 23, p. 158-165 (in Russian)
18. R. Freivalds. Speeding up recognition of certain sets by usage of random number generators. "Problemi kibernetiki ", 1979, v. 36, p. 209-224 (in Russian)
19. R. Freivalds. On principal capabilities of probabilistic algorithms in inductive inference. "Semiotika i informatika", Moscow, VINITI, 1979, v. 12, p. 137-140 (in Russian)
20. R. Freivalds and R. Wiehagen. Inductive inference with additional information. "Elektronische Informationsverarbeitung und Kybernetik (EIK)", 1979, Bd. 15, H. 4, S. 179-18
21. R. Freivalds. Finite identification of general recursive functions by probabilistic strategies. " Proc. 2nd International Conference " Fundamentals of Computation Theory "", Berlin, Akademie, 1979. p. 138-145
22. R. Freivalds. On the increase of the number of states in the process of determinization of finite probabilistic automata. "Avtomatika i Vichislitel'naja Tekhnika", 1982, No. 3, p. 39-42 (in Russian)
106
23. R. Freivalds. Trade-off between the complexity of two-way and one-way finite automata. "Automata, algorithms and languages", Kalinin, Kalinin State University, 1982, p. 163-167 (in Russian)
24. R. Freivalds. Undecidability of emptiness problem for probabilistic finite multi-tape automata. "Mathematical logics, mathematical liguistics and theory of automata", Kalinin, Kalinin State University, 1983, p. 69-74 (in Russian)
25. R. Freivalds. A characterization of capabilities of the simplest method to prove advantages of probabilistic automata over deterministic ones. "Latviiskij matematicheskij ezhegodnik", Riga, Zinātne, 1983, v.27, p.241-251 (in Russian)
26. R. Freivalds. Probabilistic limiting identification of total recursive functions in various computable numberings. "Machine recognition of regularities" Riga, Polytechnical University, 1981, p. 104-106.
27. R. Freivalds and E.B.Kinber. On extension of inferrable classes. "Bulletin of EATCS", 1983, No.20, p. 49-53
28. R. Freivalds. On capabilities of two-way finite probabilistic automata. "Theory of Finite Automata and Applications ", Riga, Zinātne, 1983, v. 14, p. 80-93 (in Russian)
29. R. Freivalds. Methods and languages to prove the power of probabilistic machines. " Information Processing'83 ( Proc. IFIP Congress'83 ), Elsevier, 1983, p. 157-162
30. R. Freivalds. Undecidability of the emptiness problem for probabilistic finite multitape automata. " Mathematical Logics, Mathematical Linguistics and Theory of Automata ", Kalinin, University Press, 1983, p. 69-74 (in Russian)
31. R. Freivalds. On two-way multihead finite probabilistic automata. "Latviiskij matematicheskij ezhegodnik ", Riga, Zinātne, 1984, v. 28, p. 224-233 (in Russian)
32. R. Freivalds. An answer to an open problem. "Bulletin of EATCS", 1984, No. 23, p. 31-32
33. R. Freivalds and E.B.Kinber. Recursivness of the enumerating functions increases the inferrabilityof recursively enumerable sets. " Bulletin of EATCS ", 1985, No. 27, p. 35-40
34. R. Freivalds and G. Lazdiņa. On reversal complexity of probabilistic and deterministic one-way Turing machines. " Complexity problems in mathematical logics ", Kalinin, University Press, 1985, p. 64-68 (in Russian)
35. R. Freivalds. On probabilistic and deterministic Turing machines with input and output. " Theory of algorithms and programs", Riga, Latvian State University, 1986, p. 4-22 (in Russian)
36. R. Freivalds. Comparison of complexity bounds for computation by probabilistic and deterministic machines. " Probabilistic automata and applications ", Kazan, University Press, 1986, p. 36-44 (in Russian)
37. R. Freivalds. Complexity of computation by one-way probabilistic Turing machines. "Cybernetics and Computer Science ", Moscow, Nauka, 1986, v. 2, p. 147-179 (in Russian)
107
38. R. Freivalds. Provable advantages in complexity of computation by probabilistic machines. " Proc. 1st World Congress of the Bernoulli Society on Mathematical Statistics and Theory of Probabilities ", Moscow, Nauka, 1986, v. 2, p.519
39. R. Freivalds and D. Taimiņa. On complexity of probabilistic finite automata recognizing omega-languages. "Logical methods in construction of effective algorithms", Kalinin, University Press, 1986, p. 92-96 (in Russian)
40. R. Freivalds, E.B.Kinber and R.Wiehagen. Probabilistic inductive inference in nonstandard numberings. Preprint No. 138. Humboldt Universitaet, Berlin, 1987
41. R. Freivalds and M.P.Chytil. Probabilistic algorithms and recognition of extensibility of words to enter a language. " Theoretical problems in programming ", Riga, University of Latvia, 1988, p. 33-50 (in Russian)
42. R. Freivalds. The minimal number or queries in decision trees. "Theoretical problems in programming ", Riga, University of Latvia, 1988, p. 120-122 (in Russian)
43. M.Miyakawa, I.Stojmenovic, T.Hikita, H.Machida and R.Freivalds. Sheffer and symmetric Sheffer Boolean functions under various functional constructions. "Journal of Information Processing and Cybernetics ", 1988, v. 24, No. 6, p. 251-266
44. R. Freivalds, E.B.Kinber and R.Wiehagen. On the power of probabilistic inductive inference in nonstandard numberings. " Journal of Information Processing and Cybernetics ", 1989, v. 25, No. 5/6, p. 239-243
45. R. Freivalds. Inductive inference of minimal programs. "Proc. 3rd Annual Workshop on Computational Learning Theory ", 1990, p. 3-20
46. R. Freivalds and M.Miyakawa. Complexity of decision trees for Boolean operators. ETL Technical Report TR-92-10, Tsukuba, Japan, 22 p.
47. R. Freivalds and M.Miyakawa. A data protection system based on the Lupanov conglomeration function. ETL Technical Report TR-92-11, Tsukuba, Japan, 5 p.
48. R. Freivalds and C.H.Smith. On the role of procrastination for machine learning. "Proc. COLT'92"
49. R. Freivalds. Complexity of probabilistic decision trees for Boolean operators. "Dagstuhl Seminar Report 45 ", 1992, p. 6-7.
50. R. Freivalds, E.B.Kinber and R.Wiehagen. Convergently versus divergently incorrect hypotheses in inductive inference machines. GOSLER Report 02/92, Technische Hochschule, Leipzig, 1992, 33p.
51. M.Kriíis and R. Freivalds. Inductive inference of total recursive functions by probabilistic and deterministic strategies. Yale University Technical Report YALE/DCS/TR-936, 29 p.
52. R. Freivalds and M. Miyakawa. Complexity of decision trees for Boolean operators. Researches of RIMS Kyoto No. 790, 1992, p. 242-248
53. R. Freivalds, E.B.Kinber and C.H.Smith. On the impact of forgetting on learning machines. "Proc. COLT'93", Santa Cruz, 1993, p.165-174
54. R. Freivalds, E.B.Kinber and C.H.Smith. On the impact of forgetting on learning machines. "Bulletin of EATCS", 1993, No. 51, p. 212-225
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55. R. Freivalds and A.G.Hoffmann. An inductive inference approach to classification. "Journal of Experimental and Theoretical Artificial Intelligence", 1994, v.6, No.1, p.283-289
56. K.Apsītis, R. Freivalds and C.H.Smith. Choosing a learning team: a topological approach. "Proc. STOC'94", 1994, Montreal, p.283-289
57. R. Freivalds, M.Karpinski and C.H.Smith. Co-learning of total recursive functions. "Proc. COLT'94", 1994, p.190-197
58. K.Apsītis, R. Freivalds and C.H.Smith. Learning real valued functions. "Proc. COLT'95", 1995, Santa Cruz,p. 170-177
59. A.Ambainis, R. Freivalds and J.Smotrovs. Inevitable gaps between upper and lower complexity bounds in inductive inference. "Proceedings of the 6-th International Conference "Information Processing and Management of Uncertainty in Knowledge-based Systems", Granada, Spain, July 1996, vol. 2, p.833-839
60. R. Freivalds, M.Alberts and C.H.Smith. Finite standardizability characterized in identification complexity terms. "Proceedings of the 6-th International Conference"Information Processing and Management of Uncertainty in Knowledge-based Systems", Granada, Spain, July 1996, vol. 3, p.1399-1403
61. A.Ambainis, R. Freivalds and J.Smotrovs. Inevitable gaps between upper and lower complexity bounds in inductive inference. "Proceedings of the Latvian Academy of Sciences, 1996, vol. 50, No. 1, p.49-54
62. R. Freivalds, M. Karpinski, and C.H.Smith. Randomization, martingales and additional information in inductive inference. "Proceedings of International Conference on Artificial Inlelligence", Kaohsiung, Taiwan, R.O.C., December 1996, p. 329-336
63. K. Apsītis, R. Freivalds, and C.H.Smith. Asymmetric Team Learning. "Proceedings of the 10th Annual Conference on Computational Learning Theory", July 6-9, 1997, Nashville, Tennessee, p. 90-95
64. R. Freivalds, E. Kinber, C.H.Smith. The functions of finite support: a canonical learning problem. "Proceedings of the 19th Annual Conference of the Cognitive Science Society", Palo Alto, Lawrence Erlbaum Associates, Mahwah, M. Shafto anto P. Langley, eds., August 1997, p. 235-240
Conference abstracts
1. R. Freivalds. Complexity of palindromes recognition by Turing machines with input. "Proc. of the 3rd Scientific student conference of the Novosibirsk State University", 1964, p. 12 (in Russian)
2. R. Freivalds. A Complexity bound for the functional completeness recognition by Turing machines. "Proc. 23rd scientific conference of the Latvian State University", 1966, p. 23 (in Russian)
3. R. Freivalds. On completeness of systems of logical elements for computation up to codings. "Proc. 8th USSR colloquium on algebra", Riga, 1967, p. 125 (in Russian)
4. R. Freivalds. Systems of logical elements complete up to codings. "Proc. International Conference on Artificial Intelligence", Tashkent, 1968, p.97-98 (in Russian)
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5. R. Freivalds. Completeness up to codings of systems of 3-valued functions. "Proc. USSR Symposium on Mathematical Logics", Alma-Ata, 1969, p. 38-39 (in Russian)
6. R. Freivalds. On precomplete classes of multi-valued functions. "Proc. USSR conference on theoretical cybernetics", Novosibirsk, 1969, p.102-103 (in Russian)
7. R. Freivalds. On computability in real time of operators with maximal memory. "Proc. conference of pedagogical institutes", Ivanovo, 1970, p. 40-42 (in Russian)
8. R. Freivalds. On strategies for prediction of recursive functions. "Proc. 2nd USSR Symposium on Mathematical Logics", Moscow, 1972, p. 49-50 (in Russian)
9. R. Freivalds. Towards comparison of capabilities of probabilistic and frequential algorithms."Proc. Internatinal Symposium on Discrete Systems", Riga, 1974, vol. 4, p. 280-287 (in Russian)
10. R. Freivalds. Functions computable in the limit. "Proc. 3rd USSR Symposium on Mathematical Logics", Novosibirsk, 1974, p. 216-218 (in Russian)
11. R. Freivalds. Effective operations on classes of total recursive functions. "Proc. 4th USSR Symposium on Mathematical Logics", Kishinew, 1976, p. 148 (in Russian)
12. R. Freivalds. A probabilistic counterpart of the reducibility. "Proc. 7th USSR symposium on logics and scientific methodology", Kiev, 1976, p. 201-205 (in Russian)
13. R. Freivalds. Running time of probabilistic machines with an isolated cut-point and other advantages over deterministic machines. "Proc. 2nd USSR symposium on probabilistic automata", Tbilisi, 1976, p. 33-34 (in Russian)
14. R. Freivalds. Probabilistic algorithms in proving computations. "Proc. USSR Symposium on artificial intelligence and automatization of research", Kiev, 1978, p. 102-104 (in Russian)
15. R. Freivalds. Reversals as complexity measure for probabilistic Turing machines. "Proc. 5th USSR Symposium on Mathematical Logics", Novosibirsk, 1979, p. 152-153 (in Russian)
16. R. Freivalds. Randomness and the theory of recursive functions. "Proc. conference on randomness and randomized search", Kemerovo, 1980, p. 105-107 (in Russian)
17. R. Freivalds. On reasons why the emptiness problem is undecidable for multi-tape finite probabilistic automata. "Proc. conference on mathematical logics in artificial intelligence", Vilnius, 1980, vol. 1, p. 173-174 (in Russian)
18. R. Freivalds. On a distinction between finite and limittingsynthesis. "Proc. conference on synthesis, testing and debugging of programs", Riga, 1981, p. 208-209 (in Russian)
19. R. Freivalds and E.B. Kinber. Criteria of distinction between types of limitting synthesis. "Proc. conference on synthesis, testing and debugging of programs", Riga, 1981, p. 128-129 (in Russian)
20. R. Freivalds. Reducibility by probabilistic algorithms. "Proc. 6th USSR Symposium on Mathematical Logics", 1982, p. 192 (in Russian)
21. R. Freivalds, E.B.Kinber, R. Wiehagen. On identifying functionals and standardizing operations. "Proc. 6th USSR Symposium on Mathematical Logics", 1982, p. 81 (in Russian)
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22. R. Freivalds, E.B.Kinber, R. Wiehagen. On advantages of probabilistic algorithms in inductive inference. "Proc. 3rd USSR Symposium on probabilistic automata", Kazan, 1983, p. 85 (in Russian)
23. R. Freivalds. Bounds in terms of constyructive ordinals for the complexity of limitting identification. "Proc. conference on methods of mathematical logics", Tallinn, 1983, p. 161-162 (in Russian)
24. R. Freivalds. Identification of recursively enumerable sets by recursive and nonrecursive enumerating functions. "Proc. 7th USSR Symposium on Mathematical Logics", Novosibirsk, 1984, p. 183 (in Russian)
25. R. Freivalds. On complexity of languages recognizable by probabilistic pushdown automata. "Proc. 7th USSR conference on theoretical cybernetics", Irkutsk, 1985 (in Russian)
26. R. Freivalds. Probabilistic inductive inference of partial recursive functions. "Proc. conference on synthesis, testing, verification and debugging of programs", Riga, 1986, v. 2, p. 122-123 (in Russian)
27. M. Alberts, R. Freivalds. On recognition of omega-languages by deterministic and probabilistic machines. "Proc. 8th USSR conference on theoretical cybernetics", Gorkij, 1988, p. 12-13 (in Russian)
28. R. Freivalds. On minimal number of queries in nondeterministic decision trees. "Proc. 8th USSR conference on theoretical cybernetics", Gorkij, 1988, p. 150 (in Russian)
28. M. Alberts, R. Freivalds. On advantages of probabilistic computations over deterministic ones in recognition of omega-languages. "Proc. 9th USSR conference on mathematical logics", Leningrad, 1988, p. 4 (in Russian)
29. M. Alberts, R. Freivalds. On communication complexity of Boolean functions."Proc. 9th USSR conference on mathematical logics", Leningrad, 1988, p. 165 (in Russian)
Pedagogical writings :
1. R. Freivalds. Mathematics, logics and paradoxes in logics. Rīga, Zinību biedrība, 1975 (in Latvian)
2. R. Freivalds. From mathematics to linguistics, a return trip. Rīga, Zinību biedrība, 1980 (in Latvian)
3. R. Freivalds, D.Taimiņa, E.B.Kinbers. Basics of computers. 1.d., 2.d., 3.d. A guidebook for teachers. Rīga, Latvijas Valsts Universitāte, 1985 (in Russian)
4. R. Freivalds, A.Kālis, D.Taimiņa, S.Pavlovs. Fundamentals of computers. A manual for teachers. Rīga, Latvijas Valsts Universitāte, 1985 (in Russian)
5. A. Auziņš, A. Brāzma, R. Freivalds et. al Why we study informatics? "Učiteļskaja gazeta", September 12, 1985 (in Russian)
6. A. Auziņš, A. Brāzma, R. Freivalds et. al Algorithms and their properties " Učiteļskaja gazeta", September 14, 1985 (in Russian)
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7. A. Auziņš, A. Brāzma, R. Freivalds et. al Algorithmic language " Učiteļskaja gazeta", September 24, 1985 (in Russian)
8. A. Auziņš, A. Brāzma, R. Freivalds et. al Algorithms for processing values " Učiteļskaja gazeta", October 31, 1985 (in Russian)
9. A. Auziņš, A. Brāzma, R. Freivalds et. al {\em Subroutines} " Učiteļskaja gazeta", January 7, 1986 (in Russian)
10. A. Auziņš, A. Brāzma, R. Freivalds et. al Stages of problem solving by computers " Učiteļskaja gazeta", January 28, 1986 (in Russian)
11. A. Averbukh, A. Auziņš, R. Freivalds et. al Algorithms for processing strings " Učiteļskaja gazeta", February 4, 1986 (in Russian)
12. A. Averbukh, A. Auziņš, R. Freivalds et. al Ordering of a linear array " Učiteļskaja gazeta", February 6, 1986 (in Russian)
13. R. Freivalds, D.Taimiņa, A.Auziņš, O.Jolkina, P.Ķikusts. Algorithmic languages and the programming language RAPIRA. A manual for teachers. Rīga, Latvijas Valsts Universitāte, 1986 (in Russian)
14. A.P. Ershov, V.Monahov, R. Freivalds et al. Teaching fundamentals of computers. Moscow, Prosveshchenie, 1986 (in Russian)
15. A.P. Ershov, V.Monahov, R. Freivalds et al. Teaching fundamentals of computers. Kishinew, Lumina, 1987 (in Moldovian, translation of [14])
16. A.P. Ershov, V.Monahov, R. Freivalds et al. Teaching fundamentals of computers.Vilnius, Sviesa, 1987 (in Lithuanian, translation of [14])
17. R. Freivalds, D.Taimiņa, E.B.Kinber. Basics of Computers. A manual for teachers. Baku, Minpros, 1986 (in Azeri, translation from [3])
18. R. Freivalds. Where computers are used and where they are not used. Rīga, Zinību biedrība, 1988 (in Latvian)
19. L. Andersone, R. Freivalds, L. Rāte. Problems in the school course of computers. "Informatika i obrazovanije", 1987, No. 5, p. 55-64 (in Russian)
20. L. Andersone, R. Freivalds, A. Raudis. Educational TV programs on computers and programming. " Computers in education ", Riga, University of Latvia, 1988, p. 68-74 (in Russian)
Popular scientific papers:
1. R. Freivalds. Switching circuits. " Kvant ", 1972, No. 2, p. 16-19, 27 (in Russian)
2. R. Freivalds. Artificial intelligence and its influence on mathematization of humanitarian sciences. "Abstracts of lectures on physics and mathematics", Rīga, Zinību biedrība, 1975, p.10-13 (in Rusian)
3. R. Freivalds. What is computational complexity theory? "Abstracts of lectures on physics and mathematics", Rīga, Zinību biedrība, 1979, p.34-36 (in Rusian)
4. R. Freivalds. Church thesis. "Latvijas Padomju Enciklopēdija", 1982, s. 2, lp. 339-340 (in Latvian)
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5. R. Freivalds. Formal grammars "Latvijas Padomju Enciklopēdija ", 1983, s. 3, lp. 361 (in Latvian)
6. R. Freivalds. Theory of inductive inference. "Latvijas Padomju Enciklopēdija ", 1983, s. 4, lp. 268 (in Latvian)
7. R. Freivalds. Computability. "Latvijas Padomju Enciklopēdija ", 1983, s. 4, lp. 393 (in Latvian)
8. R. Freivalds. Jonins Gerards. "Latvijas Padomju Enciklopēdija ", 1983, s. 4, lp. 496 (in Latvian)
9. R. Freivalds. Klokovs Jurijs. "Latvijas Padomju Enciklopēdija ", 1984, s. 5, lp. 163 (in Latvian)
10. R. Freivalds. Algorithmic problems. "Latvijas Padomju Enciklopēdija ", 1985, s. 6, lp. 493 (in Latvian)
11. R. Freivalds. Undecidability. "Latvijas Padomju Enciklopēdija ", 1986, s. 7, lp. 117 (in Latvian)
12. R. Freivalds. Nedeterministic automata. "Latvijas Padomju Enciklopēdija ", 1986, s. 7, lp. 119 (in Latvian)
13. R. Freivalds. Exhaustive search. "Latvijas Padomju Enciklopēdija ", 1986, s. 7, lp. 539 (in Latvian)
14. R. Freivalds. Recursive functions} "Latvijas Padomju Enciklopēdija “,1986,s. 8, lp. 327 (in Latvian)
15. R. Freivalds. Randomness as a source of computation. " Zinātne un Tehnika ", 1987, No.10 p. 8-10 (in Latvian)
16. R. Freivalds and L. Kacnelson. Eiþens Āriņš. "Latviiskij matematicheskij ezhegodnik", Riga, Zinātne, 1988, v. 32, p. 3-8 (in Russian)
17. R. Freivalds and J. Dambītis. Jānis Bārzdiņš, an outstanding mathematician, teacher and leader. "Izglītība un Kultūra", February 13, 1997, p. 18 (in Latvian)
18. R. Freivalds. It is possible. "Zvaigžņotā Debess", 1997, No. 4, lpp. 26-27
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Curriculum VitaeAudris Kalniņš
Audris KALNINS
Dr. Hab.Sc. Comp.The University of LatviaInstitute of Mathematics and Computer ScienceRainis boul. 29Riga, LV-1459LatviaPhone : +371 7211014Fax: +371 7820153E-mail: [email protected]
Date and place of birth: 1942, Latvia
Education:1960-1965 Undergraduate studies, Latvia State University, Faculty
of Physics and Mathematics, Mathematics1967-1970 Graduate studies, Latvia State University
Scientific degrees:
Candidate of Science (Applied Mathematics) - in 1972 from Computing Center (Novosibirsk), the Academy of Sciences of the USSR. Supervisor: Prof. J.Barzdins.
Dr. Sc. Comp. - in 1992 by nostrification procedure from the Latvian Council of Science.
Dr. Hab. Sc. Comp. - in 1997 from the Latvian University Council for Habilitation and Promotion
Employment:
1965-1972 Scientific Associate, Computer Center, Latvia State University
Since 1972 Senior Scientific Associate, Institute of Mathematics and Computer Science, the University of Latvia
Since 1995 Associate Professor, the University of Latvia
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Research and Development:
In the past, Senior investigator in a series of R&D projects, concerning programming language debuggers, automatic test case generation, specification languages (SDL) and CASE tools for telecommunication systems, specification languages (GRAPES) and CASE tools for Information systems; and also, Principal investigator in the Latvian Council of Science research grant “Specification languages and analysis facilities for real-time systems”.
Currently, senior designer in the GRADE project, related to Business system modeling languages and tools.
Courses Taught:
1972 - 1974 Theory of finite state machines1975 - 1980 Specification languages for information systemsSince 1992 GRAPES languages and toolsSince 1992 Software Engineering
List of Main Publications:
Books:
1. A.Kalnins, M.Augustons, R.Balodis, J.Barzdins et al. -Programming in PL/1 OS/360. Finances and Statistics Publishers, Moscow (1-st ed. 1979, 270p. 2-nd ed. 1984, 327 p.) (in Russian), (polish translation by PVN, Warsaw, 1988),
2. A.Kalnins, J.Barzdins, J.Strods, V.Sitsko. -Specification language SDL/PLUS and its applications. University of Latvia, 1-st ed. - 1986, 2-nd ed. -1988, 312 p.,
Papers:
1. A.Kalnins. -Statistical estimates of chromatic number for a class of graphs. Latvian Mathematics Annual, V.7, 1970, 111-125 (in Russian)
2. A.Kalnins. -Graph colouring in a linear number of steps. Kibernetika, N4, 1971, 103-111 (in Russian).
3. A.Kalnins. -Complexity bounds for graph colouring on Turing machine. Problemi Peredatsi Informacii, v.7, N4, 1971, 59-71 (in Russian).
4. A.Kalnins, J.Barzdins, J.Bicevskis. -Construction of complete sample system for program correctness testing. Theory of Algorithms and Programs, N1, University of Latvia, 1974, pp.152-187 (in Russian),
5. A.Kalnins, J.Barzdins, J.Bicevskis. -Solvable and unsolvable cases of complete sample system construction. Theory of Algorithms and Programs, N1, University of Latvia, 1974, pp.188-205 (in Russian),
6. A.Kalnins, J.Barzdins, J.Bicevskis. -Construction of complete sample system for programs with direct access, Theory of Algorithms and Programs, N2, University of Latvia, 1975, pp.123-154 (in Russian),
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7. A.Kalnins, J.Barzdins, J.Bicevskis. -Automatic construction of complete sample system for program testing. Proc. IFIP Congress '77, North Holland, 1977, pp. 57-62,
8. A.Kalnins, J.Barzdins, J.Bicevskis. -Construction of complete sample system for correctness testing. Proc. MFCS 1975, LNCS, v.32, Springer Verlag 1975, pp.1-12,
9. A.Kalnins, J.Borzovs.-Inventory of program testing ideas. University of Latvia, 1981, 55p. (in Russian),
10. A.Kalnins, J.Barzdins, A.Zarins. -On a specification language. Kibernetika N6, 1982 (in Russian),
11. A.Kalnins, M.Augustons, J.Barzdins -Function specification languages. University of Latvia, 1983, 120 p. (in Russian),
12. A.Kalnins, M.Augustons, J.Barzdins -Program testing system for PDP 11 assembley language. University of Latvia, 1984, 30p.,
13. A.Kalnins, M.Augustons, J.Barzdins -Language for program testing and specification. Tehnika sredstv svyazi, N2, 1984. (in Russian),
14. A.Kalnins, J.Borzovs. -Program testing: specification languages and automatic test generation. Kibernetika, N6, 1985 (in Russian),
15. A.Kalnins, M.Augustons, J.Barzdins. -SDL tools for rapid prototyping and testing. SDL'89. The Language at Work. Proc. 4-th SDL Forum, North Holland, 1989, pp.127-134.,
16. A.Kalnins. -SDL support environment for prototyping and testing. Proc. NWPER'90, NTH, Trondheim, 1990.
17. A.Kalnins, A.Auzins, J.Barzdins, J.Bicevskis, K.Cerans. -Automatic Construction of test sets: theoretical approach. Baltic Computer Science, LNCS v.502, Springer Verlag, 1991, pp. 286-359,
18. A.Kalnins., J.Borzovs, I.Medvedis.-Automatic construction of test sets: Practical approach. Baltic Computer Science, LNCS v.502, Springer Verlag, 1991, pp. 360-432,
19. A.Kalnins. -Global state based automatic test generation for SDL. SDL'91. Evolving Methods. Proc. 5-th SDL Forum, North Holland, 1991, pp. 303-312.
20. A.Kalnins., J.Barzdins, K.Podnieks.- GRADE V1.0: Modelling and development environment for GRAPES-86 and GRAPES/4GL: Language description. Siemens Nixdorf, 1993, 246 p.,
21. A.Kalnins, J.Barzdins, K.Podnieks, I.Etmane et al. -Unified specification language and Integrated CASE tools for information system development. Proceedings of Baltic DB'94, v2, Mokslo Aidai, Vilnius 1994, pp. 24-34,
22. A.Kalnins, J.Barzdins, K.Podnieks, I.Etmane et al. -GRADE Windows: an integrated CASE tool for information system development. Proc. SEKE'94, Knowledge Systems Institute, 1994, pp. 54-61,
23. A.Kalnins. -Extensions of GRAPES/4GL for Windows style input/output. Proc. SEKE'94, Knowledge Systems Institute, 1994, pp. 201-208.
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24. A.Kalnins, J.Barzdins, K.Podnieks, I.Etmane . -Towards Integrated Computer Aided Systems and Software Engineering Tool. Proc. of ADBIS '95, Moscow ACM SIGMOD Chapter, 1995, pp. 10-14.
25. A.Kalnins, J.Barzdins, K.Podnieks. -GRADE V2.0 (MS-Windows). Modelling and development environment for GRAPES-86 and GRAPES/4GL: Language description. Part 1. Siemens Nixdorf, 1995, 314 p.,
26. Barzdins J., Barzdins G. and Kalnins A. Rule - based approach to business modeling. Proc. 7-th International Conference on Software Engineering and Knowledge Engineering, 1995, p. 161-165.
27. A.Kalnins, J.Barzdins, K.Podnieks, I.Etmane . -Towards Integrated Computer Aided Systems and Software Engineering Tool for Information System Design.Advances in Databases and Information Systems, Springer,1996, pp. 3-11
28. A.Kalnins, J.Barzdins et al. - Business Modeling Language GRAPES-BM and Related CASE Tools - .Proceedings of Baltic DB&IS'96, Institute of Cybernetics, Tallinn, 1996.
29. A.Kalnins, J.Barzdins, A.Kalis - GRADE -BM:. Modelling and Simulation Facilities, Proceedings of NWPER'96, Aalborg University, 1996, pp. 71-86.
30. M.Alberts, A.Kalnins, D.Kalnina - Automated Testing of Telecommunication Systems , Automatic Control and Computer Science,1997
31. A. Kalnins, GRADE Version 3.0 Business Modeling Language Reference Manual.Infologistik GmbH, Munich, 1996, 102p.
32. A. Kalnins GRADE-BM V.3.0 Simulation Tutorial. Infologistik GmbH, Munich, 1996, 111p.
33. Bārzdiņš J. and Kalniņš A. Enterprise Modeling and Business Process Reengineering: Tool Support. - Proc. International Conference and Exhibition “Information Technologies and Telecommunications in the Baltic States”, Riga, 1997, pp.69-73
Conference Reports (last five years):
1. “GRADE Windows: an integrated CASE tool for information system development”, 6th International Conference on Software Engineering and Knowledge Engineering, Riga, Latvia, 1994 (with J.Barzdins, K.Podnieks et al.)
2. “Extensions of GRAPES/4GL for Windows style input/output”, 6th International Conference on Software Engineering and Knowledge Engineering, Riga, Latvia, 1994
3. “Unified specification language and Integrated CASE tools for information system development”, Baltic Workshop on Data bases,Vilnius, Lithuania, 1994, (with J.Barzdins, K.Podnieks et al.)
4. “Towards integrated computer aided systems on software engineering tool for information systems design”, Second International Workshop on Advances in Databases and Information Systems, Moscow, 1995 (with J.Barzdins, K.Podnieks, I.Etmane et al.)
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5. “Business modeling language GRAPES-BM and related CASE tools”, Second International Baltic Workshop, Tallinn, Estonia, 1996 (with J.Barzdins, A.Auzins et al.)
6. “GRADE-BM: Modelling and Simulation Facilities”, Nordic Workshop on Programing Environment Research, Aalborg, Denmark, 1996 (with J.Barzdins, A.Kalis).
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Curriculum VitaePaulis Ķikusts
Name: Paulis ĶIKUSTS, Dr. sc. Math.
Born: 1948
Education:
1971 M.Sc. - University of Latvia,.
1977 Ph.D. - Research Institute of Mathematics of Belorussian Academy of Sciences
Employment:
Currently Leading Researcher at the Institute of Mathematics and Computer Science of University of Latvia and Lecturer at the Faculty of Physics and Mathematics of University of Latvia.
A principal member of GRADE Windows developing group in the part of graphic editors.
Research directions:
Computer vision, computer graphics, graph theory, computational geometry.
Academic courses:
since 1980 Graph theory (2 credits)
since 1985 Theory of random graphs (2 credits)
since 1988 Computational geometry (2 credits)
since 1993 Computer graphics (4 credits)
since 1994 Computer graphics (2 credits)
Most important publications:
1. P.Kikusts On the existence of a hamiltonian cycle in a regular graph of degree 5, - Latvian Mathematical Yearbook, Vol. 16, "Zinatne", Riga, 1975, pp.33-38, (in Russian).
2. P.Kikusts Another algorithm determining the independence number of a graph, - EIK, 22 1986. p.157-166
3. P.Kikusts On plane transforms based recognition of planar hierarchial patterns, - in Theoretical Questions of Programming, University of Latvia, 1988, pp.108-109, (in Russian).
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4. P.Kikusts at al. Investigation and development of image recognition algorithms on the basis of TV videomemory and specialized VLSI, - Technical Report of Institute of Mathematics and Computer Science of University of Latvia for Research Institute of TV in Leningrad, 1990, (in Russian).
5. I.Etmane, P.Kikusts, P.Rucevskis. Basic principles and layout algorithms of GRADE Windows graphic editors, - Proc. of Int. Workshop on Constraints for Graphics and Visualization, Marseille, France, September 18, 1995.
6. P.Kikusts, P.Rucevskis. Layout algorithms of graph-like diagrams for GRADE Windows graphic editors, - Proc. of Symposium Graph Drawing '95, "Lecture Notes in Computer Science", vol. 1027, 1996, pp.361-364.
Prizes:
1995 Symposium Graph Drawing '95, Passau Germany: First and Third prizes in separate categories of Graph-Drawing Contest.
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Curriculum VitaeJuris Miķelsons
Date and place of birth: 1936, Riga, LatviaIdentity No.: 140536-13124Languages: Latvian, Russian, EnglishJob title: Chairman, Committee of Education, Youth and Sports, Riga City CouncilEducation:
1953 - 1956 student of Blagovescensk Pedagogical Institute (USSR)1956 - 1959 student of University of Latvia, Faculty of Physics and
Mathematics
Scientific degrees and academic titles:
1967 Dr. sc. physics, University of Latvia1988 professor, University of Latvia
1991 professor (USSR)
Employment history:1959 - 1970 assistant-assoc. professor Faculty of Physics and Mathematics,
University of Latvia;1970 - 1981 Head of division of Electrodynamics and continuous medium
mechanics1981 - 1992 assoc. professor, professor1992 - 1998 Head of division of Project management department of
Computer science, Faculty of Physics and Mathematics, University of Latvia;;
since march 1997 Chairman, Committee of Education, Youth and Sports, Riga City Council0,5 professor Department of Computer science
Publications:109 publications
Academic courses (in University of Latvia):
1959 – 1997 “Theoretical Mechanics”1959 – 1970 “Quantum Mechanics”1970 - 1980 “Magnitohydrodynamics”1992 - 1998 “Project Management”
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Curriculum VitaeKārlis Podnieks
Name Kārlis PODNIEKS, Dr. math.
Date and place of birth: 1948, Latvia
Education:
1966-1971 Undergraduate studies, State University of Latvia, Faculty of Physics and Mathematics, Mathematics
1971-1974 Graduate studies, State University of Latvia, Computer Center
Scientific Degrees:
Candidate of Science (Mathematics) - in 1979 from the Computer Center (Moscow), the Academy of Sciences of the USSR. Supervisor: Prof. J.Bārzdiņš
Dr math. - in 1992 by nostrification procedure from the Latvian Council of Science.
Employment:
1968-1971 Assistant, Institute of Electronics and Computers, the Academy of Sciences of the Latvian SSR
1974-1980 Senior Scientific Associate, Computer Center, State University of Latvia
1980-1990 Head of Divisions, Computer Center, State University of Latvia
Since 1990 Senior Scientific Associate, Institute of Mathematics and Computer Science, the University of Latvia
Research and Development:
Until 1976 K.Podnieks carried out research in computer science under the supervision of prof.J.Barzdins. He received his Dr.math. degree in 1979 for a study of some abstract models of computer program synthesis from sample computations.
In 1975-76 K.Podnieks obtained also some results in mathematical logic (the so called double-incompleteness theorem).
In 1977-1980 K.Podnieks was taking part in the Visual Dialogue System (VDS) project as the project manager of a PL/1 language compiler. VDS was used in the University of Latvia as an interactive tool for teaching PL/1 on IBM/360-like computers.
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In 1981-1987 K.Podnieks was department head and project manager of a data base system for Social Security Department of Latvia (IMS was used as basic DBMS) and some other data base systems based on IMS.
In 1987-1990 he was personal computer software laboratory head.
Since 1990 he is project manager in the GRADE project.
K.Podnieks has practical experience in:
- Borland C/C++ progamming,
- Borland Pascal with Objects progamming,
- IBM/360 assembly language progamming,
- PL/1 programming,
- IMS data bases.
Since 1973 K.Podnieks is working simultaneously as a lecturer at the University of Latvia. He has lectured for applied mathematics and computer science students.
K.Podnieks recent scientific activities are concerned with the specification languages for information systems design.
Courses Taught:
Recursive functionsProgramming in PL/1Programming in assembly languages of IBM/360 and PDP-11Data base management systems IMS and ADABAS
Mathematical logic (currently)
Fundamentals of data base systems (currently)
Information systems design (currently)
List of Main Publications
K.Podnieks has authored 22 articles in computer science, logic and foundations of mathematics. He is author of the book "Around the Goedel's theorem" (in Russian, the first edition appeared in 1981, the second extended edition - in 1992) and a number of tutorials for students (about IBM/360 assembly language programming, data base management system IMS and personal computer hardware).
Books
1. K.Podnieks. Around the Goedel's theorem. Zinatne Publishers, Riga, 1992, 192 pp. (in Russian)
Papers
1. K.Podnieks. On cut points of some probabilistic automata. "Automatika I vychisl.tehnika", 1970, 5 (in Russian)
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2. K.Podnieks. On stability measure of decompositions of stochastic matrices. "Automatika i vychisl.tehnika", 1971, 4 (in Russian)
3. K.Podnieks. On effective decomposition of stochastic matrices. "Automatika i vychisl.tehnika", 1972, 3 (in Russian)
4. K.Podnieks. Probalistic synthesis of enumerated classes of functions. "Dokl.Akad.Nauk SSSR", Tom 223 (1975), 5 (in Russian)
5. K.Podnieks. Prediction of next values of functions. "Izvestija Vysh.Uchebn.Zaved. Matematika", 1981, 5 (in Russian)
6. K.Podnieks. Platonism, intuition and the nature of mathematics. "Semiotika i informatika", Moscow, VINITI, 1990 (in Russian)
7. R.Freivalds, J.Barzdins, K.Podnieks. Inductive inference of recursive functions: complexity bounds. In: "Lecture Notes in Computer Science", 1991, vol.502.
Conference Reports
1. K.Podnieks. The double-incompleteness theorem. Proc. IV All- union conf. on mathematical logic, Kishinev, 1976 (in Russian)
2. K.Podnieks. Platonism, intuition and the nature of mathematics. "Heyting'88. Summer School & Conference on Mathematical Logic. Chaika, Bulgaria, 1988. Abstracts", Sofia, 1988
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Curriculum vitae Uģis Sarkans
Name: Uģis SarkansDate of birth: 1970Personal ID number: 020470-12658Education:1988-1993 University of Latvia, Faculty of physics and mathematics, undergraduate
student.1993-1995 University of Latvia, Faculty of physics and mathematics, graduate student.1995-1998 University of Latvia, Institute of mathematics and computer science, PhD degree
student.Employment:1989-1993 University of Latvia, Institute of mathematics and computer science, laboratory
assistant.1993-1998 University of Latvia, Institute of mathematics and computer science, research
assistant.Scientific interests: Natural language processing, programming environments, inductive synthesis, graphical editors.
Courses taught:1995, 1996 Artificial intelligence 32 acad.hrs.since 1996 Object-oriented programming and C++ 64 acad.hrs.since 1998 Programming languages 32 acad.hrs.since 1998 Declarative programming 32 acad.hrs.
17 July, 1998
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Curriculum vitaeJuris Vīksna
Date of birth: 10.03.1966
Education: 1984-1989, Latvia State University, Faculty of Physics andMathematics, student
1992-1994, University of Delaware (USA), graduate student1990-1993, University of Latvia, doctoral student
Scientific degrees:
1994 M.Sc. in computer science (UL)
1994 M.Sc. in computer science (University of Delaware)
1994 Dr.Sc. in computer science (UL)
Employment:
1989-1991 UL Faculty of Physics and Mathematics, assistant
1992-1994 University of Delaware, teaching assistant
from 1994 UL Institute of Mathematics and Computer Science, researcher
Main scientific publications:
1. J. Viksna Probabilistic inference of limiting functions with bounded number of mind changes, International Journal on Foundations of Computer Science, vol. 7, 1996, pp. 187-208.
2. J. Viksna Probabilistic limit identification up to small sets, in Proceedings of ALT’96, Lecture Notes in Computer Science, vol. 1160, 1996, pp. 312-324.
3. K. Cerans, J. Viksna Deciding reachability for planar multi-polynomial systems, in Proceedings of the 5th Workshop on Verification and Control of Hybrid Systems, Lecture Notes in Computer Science, vol. 1066, 1996, pp. 389-400.
Research areas:
Theory of inductive inference,Program verification
Courses of lectures for students:
1992 Theory of Decompositions 32 h1995 Introduction in Coding Theory 32 hfrom 1995 Algorithmic Methods of Artificial Intelligence 64 hfrom 1996 Foundations of Computer Science 32 hfrom 1995 Theory of Algorithms and Complexity 64 h
November 25, 1997 Juris Vīksna
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Curriculum VitaeMāris Vītiņš
Date and place of birth: 1948, Riga, LatviaIdentity No.: 101248-10603Languages: Latvian, Russian, German, EnglishJob title: Riga Institute of Information Technology, Training Director
Education:1966 - 1971 student of University of Latvia, Faculty of Physics and Mathematics1976 - 1980 postgraduate student of Academy of Pedagogical Sciences, Institute of Content of Education (Curriculum) and Teaching Methods, Moskow
Scientific degrees and academic titles:
1993 Dr. sc.comp., University of Latvia
1994 Leading researcher, Institute of Mathematics and Computer Science of University of Latvia
Employment history:1971 - 1973 Engeneer, Senior Engeneer, Institute of Mathematics and Computer Science of University of Latvia;1973 - 1993 Senior researcher, Head of Laboratory, Institute of Mathematics and Computer Science of University of Latvia;since 1993 Leading researcher, Institute of Mathematics and Computer Science of University of Latvia;since 1995 Training Director, Riga Institute of Information Technology
Publications:45 publications
Academic courses (in University of Latvia):
1972 – 1989 “Programming in Assembler”1974 – 1989 “Programming in PL/1”since 1989 “Teaching Methods of Informatic”since 1993 “Office Automation”
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