Convener: Houman Younessi

Software Engineering Management

Course # CISH-6050Course # CISH-6050

Lecture 1B: Lecture 1B:

Software Process Quality and Product Quality

05/07/201205/07/2012

2 CISH-6050 - Software Engineering Management

AGENDAAGENDA•Measurement Basics

- Definitions- Quantification- Types of Measurement Scales

Empirical InvestigationSoftware Engineering Measurement- Measurements Used in SE- Software Metrics

•Measurement Basics- Definitions- Quantification- Types of Measurement Scales

Empirical InvestigationSoftware Engineering Measurement- Measurements Used in SE- Software Metrics

AGENDA ……AGENDA ……

•Classifying Software Measures- Processes- Product- Resource

Measuring Software SizeMeasuring Software Quality

•Classifying Software Measures- Processes- Product- Resource

Measuring Software SizeMeasuring Software Quality

MeasurementsMeasurements

What is measurement?

Why do it?

What is measurement?

Why do it?

Measurements BasicsMeasurements Basics

•Measurement is part of many systems that govern our lives

•Measurement also plays a key role in Software and

Software Development

•Measurement is part of many systems that govern our lives

•Measurement also plays a key role in Software and

Software Development

Measurements Basics …Measurements Basics …

•Measurement – Comparison & calculations according

to a well defined set of rules

– The process by which numbers or symbols are assigned to attributes of entities in the real world in a way as to describe them according to clearly defined rules

•Measurement – Comparison & calculations according

to a well defined set of rules

– The process by which numbers or symbols are assigned to attributes of entities in the real world in a way as to describe them according to clearly defined rules

•Entity – An object (i.e. person or room) or an

event (i.e. journey or the testing phase of software) in the real world

•Attribute– Feature or property of an entity (i.e.

area or color of a room; elapsed time of testing phase)

•Entity – An object (i.e. person or room) or an

event (i.e. journey or the testing phase of software) in the real world

•Attribute– Feature or property of an entity (i.e.

area or color of a room; elapsed time of testing phase)

•Attributes and entities often interchanged in every day speech – “It’s hot today”

•OK for every day speech, but not acceptable for scientific measure– Ambiguous to say “we measure a

room”

•Attributes and entities often interchanged in every day speech – “It’s hot today”

•OK for every day speech, but not acceptable for scientific measure– Ambiguous to say “we measure a

room”

•Attributes often defined by using numbers or symbols: – Height: inches, feet, centimeters

– Price: dollars, pounds sterling, Euros

– Clothing: small, medium, large

•These numbers & symbols are abstractions used to reflect our perception of the real world

•Attributes often defined by using numbers or symbols: – Height: inches, feet, centimeters

– Price: dollars, pounds sterling, Euros

– Clothing: small, medium, large

•These numbers & symbols are abstractions used to reflect our perception of the real world

•Two Kinds of Quantification:

1.Measurement Direct quantification

2.Calculation Indirect quantification

•Two Kinds of Quantification:

1.Measurement Direct quantification

2.Calculation Indirect quantification

•Types of Measurements Scales:1.Nominal

2.Ordinal

3.Interval

4.Ratio

•Types of Measurements Scales:1.Nominal

2.Ordinal

3.Interval

4.Ratio

•Nominal– Most primitive form of measurement

– Places elements in classification scheme

– No notion of ordering of the classes

– Example: Where was the bug introduced – requirements, design, or code?

•Nominal– Most primitive form of measurement

– Places elements in classification scheme

– No notion of ordering of the classes

– Example: Where was the bug introduced – requirements, design, or code?

•Ordinal– Augments nominal scale with

information about ordering of the classes or categories

– Classes ordered with respect to the attribute

– Numbers represent ranking, so arithmetic operations not allowed

•Ordinal– Augments nominal scale with

information about ordering of the classes or categories

– Classes ordered with respect to the attribute

– Numbers represent ranking, so arithmetic operations not allowed

• Interval– Carries more information about

entities, making it more powerful than nominal and ordinal

– Captures information about size of the intervals that separates classes

– Addition and subtraction allowed, but not multiplication and division

• Interval– Carries more information about

entities, making it more powerful than nominal and ordinal

– Captures information about size of the intervals that separates classes

– Addition and subtraction allowed, but not multiplication and division

•Ratio– Most useful scale of measurements

– Most common scale in physical sciences

– Contains zero element lack of attribute

– Preserves ordering, size, and ratios

– All arithmetic can be applied

•Ratio– Most useful scale of measurements

– Most common scale in physical sciences

– Contains zero element lack of attribute

– Preserves ordering, size, and ratios

– All arithmetic can be applied

• Is LOC (Lines of Code) Ratio or Absolute scale of measure?– Obtained by ‘counting’ …

– But … is LOC the only way to measure the length of source code?

• Is LOC (Lines of Code) Ratio or Absolute scale of measure?– Obtained by ‘counting’ …

– But … is LOC the only way to measure the length of source code?

•Empirical Investigation– Empirical data vs. advice and

counsel?

– Better to rely on scientific research for objective decisions, vs. advice and counsel

•Empirical Investigation– Empirical data vs. advice and

counsel?

– Better to rely on scientific research for objective decisions, vs. advice and counsel

Empirical InvestigationsEmpirical Investigations

•Several types of Assessments– Surveys

Research in the large

– Case Studies Research in the typical

– Formal Experiments Research in the small

•Several types of Assessments– Surveys

Research in the large

– Case Studies Research in the typical

– Formal Experiments Research in the small

Software Engineering Measurements

•Computer Science provides theoretical foundations for building software

•SE focuses on implementing software in controlled and scientific manner

•Computer Science provides theoretical foundations for building software

•SE focuses on implementing software in controlled and scientific manner

Software Engineering Measurements …

•Engineering disciplines use methods based on models and theories

•Measurements are the underpinning of scientific process

•Engineering disciplines use methods based on models and theories

•Measurements are the underpinning of scientific process

• Imagine electrical, mechanical, or civil engineering without measurements?

•Measurements still viewed as luxury in Software Engineering– Done infrequently, inconsistently, and

incompletely

• Imagine electrical, mechanical, or civil engineering without measurements?

•Measurements still viewed as luxury in Software Engineering– Done infrequently, inconsistently, and

incompletely

•Measurements are essential in engineering disciplines

•Measurements essential for SE even when project not in trouble– Helps to control the project, not just

run it

•Measurements are essential in engineering disciplines

•Measurements essential for SE even when project not in trouble– Helps to control the project, not just

run it

“You cannot control what you cannot measure”

− Tom Demarco, 1982

•Measurements key for– Understanding

– Controlling

– Improving

“You cannot control what you cannot measure”

− Tom Demarco, 1982

•Measurements key for– Understanding

– Controlling

– Improving

•Scope of Software Metrics:– Cost and Effort Estimation

– Productivity Models and Measures

– Data Collection

– Quality Models and Measures

– Reliability Models

– Performance Evaluation and Models

•Scope of Software Metrics:– Cost and Effort Estimation

– Productivity Models and Measures

– Data Collection

– Quality Models and Measures

– Reliability Models

– Performance Evaluation and Models

•Scope of Software Metrics …– Structural and Complexity Models

– Management Metrics

– Evaluation of Methods and Tools

– Capability Maturity Assessments

•Scope of Software Metrics …– Structural and Complexity Models

– Management Metrics

– Evaluation of Methods and Tools

– Capability Maturity Assessments

•Direct and Indirect Measurements:– Direct measurement of an attribute

involves no other attribute or entity

– Indirect measurement of an attribute involves at least 1 other attribute or entity

•Direct and Indirect Measurements:– Direct measurement of an attribute

involves no other attribute or entity

– Indirect measurement of an attribute involves at least 1 other attribute or entity

•Direct Measurements in SE:– Length of source code

– Duration of a phase

– Number of defects found during phase

– Time a programmer spends on a project

•Direct Measurements in SE:– Length of source code

– Duration of a phase

– Number of defects found during phase

– Time a programmer spends on a project

• Indirect Measurements in SE:– Programmer productivity

– Module Defect Density

– Defect detection efficiency

– Requirements stability

– Test Effectiveness ratio

– System Spoilage

• Indirect Measurements in SE:– Programmer productivity

– Module Defect Density

– Defect detection efficiency

– Requirements stability

– Test Effectiveness ratio

– System Spoilage

Classifying Software MeasuresClassifying Software Measures

•Software Entity and Attribute Classes to Measure:– Processes: collection of software

related activities

– Products: artifacts, deliverables, or documents from process activity

– Resources: entities required by process activity - personnel, materials

•Software Entity and Attribute Classes to Measure:– Processes: collection of software

related activities

– Products: artifacts, deliverables, or documents from process activity

– Resources: entities required by process activity - personnel, materials

Classifying Software MeasuresClassifying Software Measures

•Attributes for each class of entity:– Internal: measured purely in terms of

the process, product, or resource itself

– External: measured only with respect to how the process, product or resource relates to its environment

•Attributes for each class of entity:– Internal: measured purely in terms of

the process, product, or resource itself

– External: measured only with respect to how the process, product or resource relates to its environment

Classifying Software Measures

ProductsSpecifications size, reuse, modularity, functionality, ... comprehensibility, maintainability, ...

Design size, reuse, modularity, coupling, cohesiveness, ...

quality, complexity, maintainability, ...

Code size, reuse, modularity, coupling, functionality, ...

reliability, usability, maintainability, ...

--- --- ---ProcessesDetailed Design time, effort, number of specification faults

found, ...cost, cost-effectiveness, ...

Testing time, effort, number of coding faults found, ...

cost, cost-effectiveness, stability, ...

---- --- ---ResourcesPersonnel age, price, ... productivity, experience,

intelligence, ...Software price, size, ... usability, reliability, ...Hardware price, speed, memory size, ... reliability, ...

ENTITIES INTERNAL EXTERNALATTRIBUTES

Measuring Software SizeMeasuring Software Size

•Difficulties in estimating software size– Simple measures that don’t reflect

effort, productivity, and cost are rejected

– Define a fundamental set of attributes for software size; each attribute captures key aspect of software size

•Difficulties in estimating software size– Simple measures that don’t reflect

effort, productivity, and cost are rejected

– Define a fundamental set of attributes for software size; each attribute captures key aspect of software size

Measuring Software Size …Measuring Software Size …

•Fenton & Pfleeger suggestion for measuring software size:– Length: physical size of product

– Functionality: measures functions

– Reuse: amount of product reused

– Complexity (efficiency): interpretation of complexity: Problem, Algorithmic, Structural, Cognitive

•Fenton & Pfleeger suggestion for measuring software size:– Length: physical size of product

– Functionality: measures functions

– Reuse: amount of product reused

– Complexity (efficiency): interpretation of complexity: Problem, Algorithmic, Structural, Cognitive

Measuring Software QualityMeasuring Software Quality

•McCall and Cavano Quality Framework– Developed in 1978

– Basis for ISO 9126 Standard

– Same factors defined in 1970s still used today

•McCall and Cavano Quality Framework– Developed in 1978

– Basis for ISO 9126 Standard

– Same factors defined in 1970s still used today

Measuring Software Quality …Measuring Software Quality …

• ISO 9126 Standard Quality Model– Proposed in 1992

– Provides quality definition

– Six quality factors: Functionality, Reliability,

Efficiency, Usability, Maintainability, Portability

• ISO 9126 Standard Quality Model– Proposed in 1992

– Provides quality definition

– Six quality factors: Functionality, Reliability,

Efficiency, Usability, Maintainability, Portability

Measuring Software Quality …Measuring Software Quality …

•Per Standard, any software quality can be defined in terms of 6 factors

•Quality factors not included:– Correctness, Integrity, Flexibility,

Testability, Reusability, Interoperability

•Per Standard, any software quality can be defined in terms of 6 factors

•Quality factors not included:– Correctness, Integrity, Flexibility,

Testability, Reusability, Interoperability

RecapRecap•Measurements Basics

•Empirical Investigation

•Software Engineering Measurements

•Classifying Software Measures

•Measuring Software Size

•Measuring Software Quality

•Measurements Basics

•Empirical Investigation

•Software Engineering Measurements

•Classifying Software Measures

•Measuring Software Size

•Measuring Software Quality

ReferencesReferences• R. S. Pressman, Software Engineering: A

Practitioner's Approach, 5th ed., McGraw-Hill, New York, 2001

• N. E. Fenton, S. L. Pfleeger, Software Metrics: A Rigorous and Practical Approach, 2nd ed., International Thomson Computers Press, Boston, MA, 1996

• R. S. Pressman, Software Engineering: A Practitioner's Approach, 5th ed., McGraw-Hill, New York, 2001

• N. E. Fenton, S. L. Pfleeger, Software Metrics: A Rigorous and Practical Approach, 2nd ed., International Thomson Computers Press, Boston, MA, 1996

Convener: Houman Younessi

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Transcript of Convener: Houman Younessi

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