DIB 1 Component characterization: proposal and empirical assessment Pasquale Ardimento – Phd...

DIB 1

Component characterization:proposal and empirical

assessmentPasquale Ardimento – Phd Candidate

Serlab - Dept of Informatics - University of BariRCost Bari

[email protected] of Computation, UMISTManchester 16th September, 2004

mailto:[email protected]

Component Characterization

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Component-based Software Development

Component-Based Software Engineering (CBSE) promises to reduce complexity and cost of software processes

but it introduces difficulty in identifying the most appropriate

components, which satisfy specific requirements for a target Components-Based System (CBS)

difficulty in learning the component features


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Impact of component choice

The choice of the adequate component is a critical activity because of asynchronous evolutions between CBS and

components integrated in it various and numerous features of both the

organizations and of the systems to develop

the most significant aspectsof components must be known


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Our research

perform empirical studies, aimed at identifying the most significant or relevant characteristics of components

we have identified a set of component characteristics Adequacy Adoption cost Familiarity Support


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Purpose

evaluate the effectiveness of this set wrt a maintainability quality factor

To this end a quality factor in the CBS has been identified the effectiveness of component characteristics

has been evaluated wrt the maintainability quality factor


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Post-Mortem Analysis

Data of three industrial CBSs SICOD: a CBS supporting the qualification of education

and scientific services offered by the University of Bari DiPNET: a Web-Portal supporting different companies

cooperating for the development of a project Portal: the Web-Portal currently used by University of

Bari; it provides a unique point of access to a number of services and information the university offers to its stakeholders

The changes concerned corrective, adaptive and perfective maintenance


DIB 7

Component Characteristics and Metrics...

Adequacy Functional coverage - the percentage of the

CBS functionalities provided by a component wrt to the total number of functionalities the CBS provides

Compliance - the percentage of the CBS functionalities provided by a component wrt to the total number of functionalities the component makes publicly available


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...Component Characteristics and Metrics

Adoption cost Training time - the working time spent for

training people involved in the integration of components

Familiarity the understanding of a component

Support the level of support provided by the vendor


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Metrics and measurement scales

Characteristic Metrics ScaleAdequacy Functional

CoverageRatio (percentage)

Compliance Ratio (percentage)

Adoption cost Training cost Ratio (working days)

Familiarity Familiarity Ordinal (Low, Medium, High)

Support Support Ordinal (Low, Medium, High)


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Quality factor

Mean Maintenance Effort (MME) MMEj represents the effort spent to satisfy maintenance

requests in the j-th component of the CBS

whereMEi,j is the effort spent for satisfying the i-th maintenance

request of the j-th componentr is the total number of maintenance requestsn is the total number of components in the CBS

nMME

r

iji

j

ME 1

,


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Normalization

Values assumed by TT and MME measures are very different among the three projects

these factors had to be normalized

Normalization factor: and so we have:

n

jjVNF

1

n

jj

jj

TT

TTNTT

1

n

jj

jj

MME

MMENMME

1


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Research Questions

Is there any correlation between characterization metrics and quality factor metrics?

if so, are the relationships due to specific features of the projects, or are they independent from them?

Investigation

Training timeFunctional Coverage

ComplianceFamiliaritySupport

Mean Maintenance Effort


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Mutual Independence of characterization measures

FunCov Compl NTT Familiarity Support

FunCov 0,056 0,554 0,900 0,238

Compl 0,056 0,213 0,272

NTT 0,554 0,213 0,186 0,058

Famil. 0,900 0.985 0,186 0,456

Support 0,238 0,272 0,058 0,456

Results show that characterization measures are independent from each other


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Relationship between NMME and characterization measures

Variables P-level Correlation

Functional Coverage 0,502

Compliance 0,111 0,413 NO

NTT 0,634

Familiarity 0,953 0,015 NO

Support -0,687

0,047 YES

0,008 YES

0,003 YES


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Differences among projects …

Are the relationships between characterization metrics and quality factors metrics due to specific features of the projects or are they independent from them?

H0: null hypothesis some statistically significant difference exists among the

three projects with respect to those measures

H1: alternative hypothesis no statistically significant difference exists among the

three projects with respect to those measures


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… Differences among projects

Variable

P-level among projects

SICOD-DiPNET SICOD-Portal DiPNET-PortalSICOD-DiPNET-Portal

FunCov 0,070 0,738 0,794 0,254

NTT 0,401 0,317 0,191 0,321

Support 0,4385 0,404 0,695 0,475

NMME 0,518 0,504 0,794 0,745

Correlations are independent from specific features of the three projects


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Correlation between component characteristics & MME

Functional Coverage & NMME The higher is Functional Coverage the higher is the probability that a

change in CBS impacts that component Lesson learned: CBS functionality should be concentrated over a single

aspect of the application domain

Training Time & NMME components vendors propose training period depending on intrinsic

difficulty in managing the components Lesson learned: High training usually indicates the complexity of

understanding a component and this implies high maintenance effort

Support & NMME problems faced during maintenance can be faced making use of the

provided support Lesson learned: a deep knowledge of the component is necessary to

avoid the risk that the offered TT is not adequate for comprehending the needed component


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Absence of correlation

Compliance Maintenance effort of a component does not

depend on the amount of its usage but on the component itself

Familiarity During maintenance activity further unfamiliar

aspects can be required even when the developer and the maintainer are the same person


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Effectiveness of the proposed set of characteristics

The metrics Functional coverage Training time Support

resulted to be effective in characterizing the MME quality factor of Components to be maintained in a CBS


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Threats

Following threats have been avoided randomness and irrelevancies of people, tools

and processes used within all projects heterogeneity of experimental subjects the treatment is unique for all project

Following threats have not been avoided Reliability of measures Set of experimental subjects Set of experimental objects


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Future Works…

Since the current study concerned only three heterogeneous projects some threats have been poorly considered

further investigations are needed to analyse further characteristics and quality factors, which

can be meaningful for choosing components validate the cause – effect relationship between

characteristics and maintenance effort it will also be necessary to organize metrics

collection through more effective techniques and tools than interviews


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…Future Works

Following characteristics have still to be investigated Integration technique Interface stability portability Maintenance effort (a greater detail) Rating (open source) Adherence to standards (open source)


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Publications on this topic

Bianchi A., Caivano D., Conradi R., Jaccheri L., Torchiano M., Visaggio G., “COTS Products Characterization: Proposal and Empirical Assessment”, in R.Conradi and A.I. Wang (Eds.), Empirical Methods and Studies in Software Engineering – Experiences from ESERNET, Lecture Notes in Computer Science 2765 (2003), 233-255.

P.Ardimento, A.Bianchi, G.Visaggio, “Maintenance-oriented selection of software components”, CSMR2004, Tampere Finland, March: 24-26, 2004

P.Ardimento, T. Baldassarre, A. Bianchi, “Verso una caratterizzazione delle Componenti Software”, AICA2004, Benevento Italy, September 2004


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SICOD

A CBS supporting the qualification of education and scientific services offered by the University of Bari

Components integrated in it are Oracle 9i Oracle Internet Application Server 9i Oracle Report Builder and Crystal Report Applix iEnterprise Plumtree Corporate Portal 4.5


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DiPNET

a Web-Portal supporting different companies cooperating for the development of a project

Components integrated in it are SQL Server 7 SNITZ Forum DatePicker MS ADO, COM objects Internet Information Services (IIS) MS Index Server (IIXSO) MS Collaboration Data Objects for NT (CDONTS)


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Portal

The Web-Portal currently used by University of Bari provides a unique point of access to a number of

services and information the university offers to its stakeholders

Components integrated in it are SICOD SIANAR Questionnaire Oracle Portal Decision Script

DIB 1 Component characterization: proposal and empirical assessment Pasquale Ardimento – Phd...

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