[Book Cover]

Software Measurement: A Visualization Toolkit for Project Control and Process Improvement, 1/e

Dick B. Simmons, Texas A&M University, College Station, Texas
Hewlett-Packard Professional Books

Published November, 1997 by Prentice Hall PTR (ECS Professional)

Copyright 1998, 384 pp.
Cloth
ISBN 0-13-840695-2
$57.00


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[Preface]





Visualize software project success with PAMPA! PAMPA is Project Attribute Monitoring and Prediction Associate, a powerful on-line tool for gathering data and measuring, predicting, and tracking the objects, attributes and relationships at the heart of software development. With PAMPA you can:

  • Increase customer satisfaction
  • Reduce defects
  • Improve productivity
  • Decrease costs
The key is visualization. PAMPA gives form to the concepts and metrics that many developers have considered not merely invisible, but unvisualizable. Using the techniques explained in Software Measurement, you can use PAMPA to gain control over the parallel cycles of project control and process improvement.

Project attributes can be displayed as:
  • Graphical trees
  • Tables
  • Radar charts
  • 2-D graphs
  • 3-D graphs
Software Measurement begins with an overview of software process visualization. Quality systems criteria and standards are applied to the concepts of life cycle processes and project object classes.

With this foundation, the discussion goes on to specific models and metrics, including:
  • Scale
  • Development Time
  • Productivity
  • Quality
  • Reliability
  • Usability
Verification, validation, and testing techniques complete the picture. Appendices include a complete Users Manual for PAMPA and a guide to its object classes.

Software Measurement will be a valuable asset for software developers, team leaders, and project managers, as well as students of software engineering, and anyone involved in software metrics and process improvement.
@ The accompanying CD-ROM, for use on Windows' NT 3.5 or later and Windows 95, contains everything you need to put PAMPA to work on your next software project.



(NOTE: Each chapter begins with an Introduction and concludes with a Summary). I. SOFTWARE PROCESS VISUALIZATION.
    1. Introduction.

      Hardware/Software Evolution. Successes. Failures. Process Improvement Practices. How to Use This Book.

    2.Quality Systems Criteria and Standards.

      Deming Methodology. Department of Defense Software Processed. Assessment and Evaluation Programs. SEI Software Process Assessment Program. SEI Software Capability Evaluation (SCE) Program. SEI Software Process Maturity Framework. Software Capabilities Evaluation (SCE) Grading. SEI Assessment and Evaluation Programs Effectiveness. SEI Measurement, Prediction, and Improvement. Malcolm Baldrige National Quality Award. Standard Process Models. Standards. Standards Organizations. International Standards Organization (ISO). American National Standards Institute (ANSI). Institute of Electrical and Electronics Engineers (IEEE). ISO 9000 Quality Standards. Benefits of ISO 9000. ISO 9000 for Software Development. ISO 9000 Standards Elements. ISO 9000 Measurement, Prediction, and Improvement. IBM Software Quality Improvement Program. The Iron Triangle. Four-Stage Maturity Framework. Innovations.

    3. Project Visualization.

      Software Project. Project Control. Improvement. Visualization.

    4. Life Cycle Processes.

      Software Life Cycle Models. Early SLCs (Presoftware Engineering to 1968. Black Box SLC (1968 to 1985). Industry Projects. Government Projects. Process SLC (1985 to the Present). Spiral SLC. Natural Milestone SLC. Software Life Cycle Process. Process. IEEE SLC Process Model. Continuous Process Improvement.

    5. Project Object Classes.

      Notation. Project. Supplier. Customer. Organization. Software Product.

II. MODELS AND METRICS.
    6. Size.

      Volume. Volume Bulk Attributes. Bytes. VolumeSoftSciCalculate. SLOC. SSCalculate(SourceFiles). SS(RequirementsFiles, DesignFiles, and DocumentFiles). ChunksCalculate. FunctionPointsPredict. ObjectPointsPredict. Equivalent Volume. Unique Volume. UniqueSLOC. UniqueReferenceSLOC. UniqueNCSLOC. UniqueReferenceNCSLOC. Structure. Decisions. CyclomaticNumberCalculate. EssentialComplexity. NestingDepth. InheritanceDepth. SourceLiveVariablesCalculate. ThresholdLiveVariables. SpanLiveVariables. SourceLiveVariablesPerExecutableSS. ThresholdLiveVariablesPerExecutableSSCalculate. SpanLiveVariablesPerExecutableSSCalculate. Spans. Knots. Pairs. RelativePercentageUsagePairs. Triples. RelativePercentageUsageTriples. InformationFlow1Calculate. InformationFlow2Calculate. InformationFlow3Calculate. Rework. TurmoilCalculate.

    7. Effort.

      Dominators. Effort Prediction Models. Historical/Experimental Models. TRW Wolverton Model. Brooks Model. IBM Albrecht Function Point Model. Statistically Based Models. Linear Statistical Models. Nelson 1966 Model. Nelson 1970 Model. Farr and Zagorski Model. Nonlinear Statistical Models. Theoretically Based Models. Brooks Work Partition Model. Simmons Communications Model. Halstead Software Science Model. Putnam Resource Allocation Model. Composite Models. Boehm COCOMO and COCOMO 2.0 Models. Jensen Model. COPMO Model.

    8. Development Time.

      Software Science Development Time. Nominal Development Schedule Prediction. Development Schedule Compression. Minimum Development Time. Team Minimum Development Time. Project Minimum Development Time. Selection of Software Development Schedule. Schedule Slippage.

    9. Productivity.

      Productivity Measurement. Productivity Prediction. Productivity Cost Drivers. Overall Project Attributes. Salary. Development Schedule Constraints. Project Life Cycle Process. Organization Attributes. Management Quality. Lead Designer. Individual Developers. Number of People. Personnel Turnover. Communications. SoftwareProduct Attributes. Volume. Documentation. Source Language. Complexity. Type of Application (Includes Required Reliability). Work Breakdown Structure. Supplier Attributes. Software Reuse. Customer Attributes. Interface. Requirements Volatility.

    10. Quality.

      Definition of Quality. Quality Versus Productivity. Developing Software Quality: Usability. Developing Software Quality: Features. Developing Software Quality: Reliability. Total Quality Tools. An Additional Note on Developing Software Quality: Total Quality Management.

    11. Reliability.

      Failures, Faults, and Bugs. Environment. Operational Profile. Software Reliability. Characteristics of Software. The Stochastic Models. Notation. Jelinski-Moranda (JM) Model. Schick and Wolverton (SW) Model. Littlewood (L) Model. Weibull Order Statistics (W) Model. Ross (R) Model. Bayesian JM Models (BJM). Goel-Okumoto (GO) Model. Nonhomogeneous Poisson Process Models. Musa's Basic Execution Time (Musa's Basic) Model. Logarithmic Poisson (LP) Model. The Nonstochastic Software Reliability Models. Input-domain-based Model. Fault-seeding Model. Software Life Cycle Costs. Reliability Cost. Reliability-related Software Cost Models. Software Reliability and Cost.

    12. Verification and Validation Testing.

      Test Planning and Strategy. White-box Testing versus Black-box Testing. Orderly Testing Processes. Unit Test and System Test. Feature Test. Qualification Test. Installation Test. Regression Test. Software Testing Integrated Environment. Test Case Development. Test Case Development Tools. Test Data Management Tool. Test Execution Tools. Managing Testing Activities and Results. Test Activity Monitor Tools.

    13. Usability.

      The Usability Problem. Definition of Usability. Designing for Usability. Formal Iterative Design Process for Usability. Interface. Physical Factors. Test Procedures
III. VISUALIZATION TOOL.
    15. Project Attribute Monitoring and Prediction Associate (PAMPA).

      Overview. Project Visualization. Control and Improvement Cycles.

    Appendix A-PAMPA Object Classes.
    Appendix B-PAMPA Users Manual.
    Section 1-Installation and Setup.

      Statement of Copyright and Limitations of Liability. Installing PAMPA. Deinstalling PAMPA. Installing and Configuring ODBC (Optional). ODBC Update Installation. ODBC Data Source Setup (Optional). PAMPA Manuals.

    Section 2-Pampa Tutorial.

      Introduction to Pampa. Setting Up Your Project. Gathering Project Data. Plotting the Project Data.

    Section 3-Object Editor Reference.

      Introduction. Creating a Project. The Icon Menu. Creating the Project Tree. The Supplier. The Organization. Software Product. The Customer. Completion of a Project Tree.

    Section 4-Metric Plot Generator Reference.

      Dialog Reference. Terminology. Metric Plot Generator Main Dialog. New Plot Dialog. Project Drop-Down. Project Category Group Box. Sequence Buttons. Software Product Dialog. Software Product Drop-Down. Software Category Group Box. Plot Specification Dialog. Chart Type Group Box. X Axis for 2D Chart Group Box. X Axis for 3D Chart Group Box. Radar Chart Item Group Box. Version Dialog. Version Drop-Down. Subsystem Dialog. Subsystem Drop-Down. Source File Dialog. File Name Drop-Down. Metrics Dialog. Metrics List Box. Metric List Configuration Dialog. Current Metrics List Box. Metrics Available Drop-Down. Plot Preferences Dialog. Sorting Group Box. Sort by Drop-Down. Plot Options Group Box. Multiple Charts Check Box. Max Items Spinner. Chart Labels Group Box. Chart Title Edit Box. Settings Dialog. Skip Dialogs Check Boxes. Metric Plot Generator Error Messages. Plot Reference. Sequence Flow Chart. Plot Window. Chart Menu Bar. Save Menu Item. Print Menu Item. Show Data Menu Item. Locked Menu Item. Return Menu Item. Plot Window with Multiple Charts. Limitations and Problems. Averages per Source File. Count Metrics.


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