9780071502443

Applied Software Measurement Global Analysis of Productivity and Quality

by
  • ISBN13:

    9780071502443

  • ISBN10:

    0071502440

  • Edition: 3rd
  • Format: Paperback
  • Copyright: 2008-05-02
  • Publisher: McGraw-Hill Education
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Summary

New coverage of: Extreme Programming (XP); Enterprise Resource Planning (ERP); Object technology; client/server architecture; multimedia; software reusability; reengineering and outsourcing; Sarbanes-Oxley

Author Biography

Capers Jones is a renowned author, consultant, and speaker. He was the founder and chairman of Software Productivity Research (SPR), where he retains the title of Chief Scientist Emeritus. Jones is the author of Estimating Software Costs, Second Edition.

Table of Contents

Forewordp. xiii
Preface to the Third Editionp. xvii
Acknowledgmentsp. xxxi
Introductionp. 1
Applied Software Measurementp. 2
Planning and Estimationp. 3
Management and Technical Staffsp. 4
Organization Structuresp. 4
Methodologies and Toolsp. 4
The Office Environmentp. 5
Reusabilityp. 5
The Essential Aspects of Applied Software Measurementp. 6
What Do Companies Measure?p. 17
Benchmarks and Industry Measuresp. 22
Measurement and the Software Life Cyclep. 44
The Structure of a Full Applied Software Measurement Systemp. 48
The Sociology of Software Measurementp. 53
The Sociology of Data Confidentialityp. 54
The Sociology of Using Data for Staff Performance Targetsp. 55
The Sociology of Measuring One-Person Projectsp. 56
The Sociology of MIS vs. Systems Softwarep. 57
The Sociology of Measurement Expertisep. 57
Justifying and Building an Applied Software Measurement Functionp. 58
Applied Software Measurement and Future Progressp. 66
Suggested Readingsp. 67
Additional Readings on Software Measurement and Metricsp. 68
The History and Evolution of Software Metricsp. 71
Evolution of the Software Industry and Evolution of Software Measurementsp. 72
The Cost of Counting Function Point Metricsp. 78
The Paradox of Reversed Productivity for High-Level Languagesp. 87
The Varieties of Functional Metrics Circa 2008p. 104
Variations in Application Size and Productivity Ratesp. 159
Future Technical Developments in Functional Metricsp. 164
Summary of and Conclusions About Functional Metricsp. 172
Software Measures and Metrics Not Based on Function Pointsp. 173
Suggested Readings on Measures and Metricsp. 182
United States Averages for Software Productivity and Qualityp. 185
Sources of Possible Errors in the Datap. 190
Significant Software Technology Changes Between 1990 and 2008p. 226
Changes in the Structure, Format, and Contents of the Third Editionp. 244
Variations in Software Development Practices Among Seven Sub-Industriesp. 256
Ranges, Averages, and Variances in Software Productivityp. 268
The Impact of Technology on Software Productivity and Quality Levelsp. 322
Technology Warnings and Counterindicationsp. 342
Using Function Point Metrics to Set "Best in Class" Targetsp. 344
The Mechanics of Measurement: Building a Baselinep. 351
Software Assessmentsp. 352
Software Baselinesp. 356
Software Benchmarksp. 357
What a Baseline Analysis Coversp. 378
Developing or Acquiring a Baseline Data Collection Instrumentp. 380
Administering the Data Collection Questionnairep. 383
Analysis and Aggregation of the Baseline Datap. 430
Suggested Readingsp. 431
Additional Readingsp. 431
Measuring Software Quality and User Satisfactionp. 433
New Quality Information Since the Earlier Editionsp. 437
Quality Control and International Competitionp. 451
Defining Quality for Measurement and Estimationp. 454
Five Steps to Software Quality Controlp. 458
Software Quality Control in the United Statesp. 460
Measuring Software Defect Removalp. 471
Measuring Defect Removal Efficiencyp. 475
Finding and Eliminating Error-Prone Modulesp. 480
Using Metrics to Evaluate Test-Case Coveragep. 481
Using Metrics for Reliability Predictionp. 482
Measuring the Costs of Defect Removalp. 483
Evaluating Defect Prevention Methodsp. 487
Measuring Customer-Reported Defectsp. 488
Measuring Invalid Defects, Duplicate Defects, and Special Casesp. 491
Measuring User Satisfactionp. 492
Combining User Satisfaction and Defect Datap. 499
Summary and Conclusionsp. 501
Reading Listp. 501
Suggested Readingsp. 507
Additional References on Software Quality and Quality Measurementsp. 507
Measurements, Metrics, and Industry Leadershipp. 509
What Do Companies Measure?p. 511
Measures and Metrics of Industry Leadersp. 529
Measures, Metrics, and Innovationp. 532
Measurements, Metrics, and Outsource Litigationp. 535
Measurements, Metrics, and Behavioral Changesp. 536
Topics Outside the Scope of Current Measurementsp. 542
Cautions Against Simplistic and Hazardous Measures and Metricsp. 543
Commercial Software Measurement Toolsp. 546
Summary and Conclusionsp. 547
Suggested Readings on Measurement and Metricsp. 548
Summary of Problems in Software Measurementp. 549
Synthetic vs. Natural Metricsp. 550
Ambiguity in Defining the Nature, Scope, Class, and Type of Softwarep. 552
Ambiguity in Defining and Measuring the Activities and Tasks of Software Projectsp. 561
False Advertising and Fraudulent Productivity Claimsp. 564
The Absence of Project Demographic and Occupation Group Measurementp. 566
Ambiguity in the Span of Control and Organizational Measurementsp. 567
The Missing Link of Measurement: When Do Projects Start?p. 568
Ambiguity in Measuring Milestones, Schedules, Overlap, and Schedule Slippagep. 568
Problems with Overlapping Activitiesp. 573
Leakage from Software Project Resource Tracking Datap. 573
Ambiguity in Standard Time Metricsp. 575
Inadequate Undergraduate and Graduate Training in Software Measurement and Metricsp. 578
Inadequate Standards for Software Measurementp. 579
Lack of Standardization of "Lines of Source Code" Metricsp. 580
The Hazards and Problems of Ratios and Percentagesp. 589
Ambiguity in Measuring Development or Delivery Productivityp. 590
Ambiguity in Measuring Complexityp. 593
Ambiguity in Functional Metricsp. 594
Ambiguity in Quality Metricsp. 599
Ambiguity with the Defects per KLOC Metricp. 599
Ambiguity with the Cost per Defect Metricp. 600
Failure to Measure Defect Potentials and Defect Removal Efficiencyp. 602
The Problems of Measuring the Impact of "Soft" Factorsp. 603
Problems in Measuring Software Valuep. 607
Lack of Effective Measurement and Metrics Automationp. 609
Social and Political Resistance to Software Measurementsp. 617
Ambiguity in Software Measurement and Metrics Terminologyp. 620
Failure to Use Metrics for Establishing Goals and Targetsp. 624
Summary and Conclusionsp. 629
Suggested Readingsp. 630
Additional References on Software Measurementsp. 632
Rules for Counting Procedural Source Codep. 635
Project Source Code Counting Rulesp. 637
General Rules for Counting Code Within Applicationsp. 639
Examples of the SPR Source Code Counting Rulesp. 640
Software Productivity Research COBOL-Counting Rulesp. 642
Indexp. 645
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