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E-raamat: Applied Software Measurement: Global Analysis of Productivity and Quality

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  • Formaat: 696 pages
  • Ilmumisaeg: 11-May-2008
  • Kirjastus: Osborne/McGraw-Hill
  • Keel: eng
  • ISBN-13: 9780071643863
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Applied Software Measurement: Global Analysis of Productivity and QualitySuurem pilt
  • Formaat: 696 pages
  • Ilmumisaeg: 11-May-2008
  • Kirjastus: Osborne/McGraw-Hill
  • Keel: eng
  • ISBN-13: 9780071643863
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Effectively forecast, manage, and control software across the entire project lifecycle

Accurately size, estimate, and administer software projects with real-world guidance from an industry expert. Fully updated to cover the latest tools and techniques, Applied Software Measurement, Third Edition details how to deploy a cost-effective and pragmatic analysis strategy. You will learn how to use function points and baselines, implement benchmarks and tracking systems, and perform efficiency tests. Full coverage of the latest regulations, metrics, and standards is included.





Measure performance at the requirements, coding, testing, and installation phases

Set function points for efficiency, cost, market share, and customer satisfaction

Analyze quality and productivity using assessments, benchmarks, and baselines

Design and manage project cost, defect, and quality tracking systems

Use object-oriented, reusable component, Agile, CMM, and XP methods

Assess defect removal efficiency using unit tests and multistage test suites
Foreword xiii
Preface to the Third Edition xvii
Acknowledgments xxxi
Chapter
1. Introduction		 1
Applied Software Measurement
2
Planning and Estimation
3
Management and Technical Staffs
4
Organization Structures
4
Methodologies and Tools
4
The Office Environment
5
Reusability
5
The Essential Aspects of Applied Software Measurement
6
What Do Companies Measure?
17
Benchmarks and Industry Measures
22
Measurement and the Software Life Cycle
44
The Structure of a Full Applied Software Measurement System
48
The Sociology of Software Measurement
53
The Sociology of Data Confidentiality
54
The Sociology of Using Data for Staff Performance Targets
55
The Sociology of Measuring One-Person Projects
56
The Sociology of MIS vs. Systems Software
57
The Sociology of Measurement Expertise
57
Justifying and Building an Applied Software Measurement Function
58
Applied Software Measurement and Future Progress
66
Suggested Readings
67
Additional Readings on Software Measurement and Metrics
68
Chapter
2. The History and Evolution of Software Metrics		 71
Evolution of the Software Industry and Evolution of Software Measurements
72
The Cost of Counting Function Point Metrics
78
The Paradox of Reversed Productivity for High-Level Languages
87
The Varieties of Functional Metrics Circa 2008
104
Variations in Application Size and Productivity Rates
159
Future Technical Developments in Functional Metrics
164
Summary of and Conclusions About Functional Metrics
172
Software Measures and Metrics Not Based on Function Points
173
Suggested Readings on Measures and Metrics
182
Chapter
3. United States Averages for
Software Productivity and Quality
185
Sources of Possible Errors in the Data
190
Significant Software Technology Changes Between 1990 and 2008
226
Changes in the Structure, Format, and Contents of the Third Edition
244
Variations in Software Development Practices Among Seven Sub-Industries
256
Ranges, Averages, and Variances in Software Productivity
268
The Impact of Technology on Software Productivity and Quality Levels
322
Technology Warnings and Counterindications
342
Using Function Point Metrics to Set "Best in Class" Targets
344
Chapter
4. The Mechanics of Measurement: Building a Baseline		 351
Software Assessments
352
Software Baselines
356
Software Benchmarks
357
What a Baseline Analysis Covers
378
Developing or Acquiring a Baseline Data Collection Instrument
380
Administering the Data Collection Questionnaire
383
Analysis and Aggregation of the Baseline Data
430
Suggested Readings
431
Additional Readings
431
Chapter
5. Measuring Software Quality and User Satisfaction		 433
New Quality Information Since the Earlier Editions
437
Quality Control and International Competition
451
Defining Quality for Measurement and Estimation
454
Five Steps to Software Quality Control
458
Software Quality Control in the United States
460
Measuring Software Defect Removal
471
Measuring Defect Removal Efficiency
475
Finding and Eliminating Error-Prone Modules
480
Using Metrics to Evaluate Test-Case Coverage
481
Using Metrics for Reliability Prediction
482
Measuring the Costs of Defect Removal
483
Evaluating Defect Prevention Methods
487
Measuring Customer-Reported Defects
488
Measuring Invalid Defects, Duplicate Defects, and Special Cases
491
Measuring User Satisfaction
492
Combining User Satisfaction and Defect Data
499
Summary and Conclusions
501
Reading List
501
Suggested Readings
507
Additional References on Software Quality and Quality Measurements
507
Chapter
6. Measurements, Metrics, and Industry Leadership		 509
What Do Companies Measure?
511
Measures and Metrics of Industry Leaders
529
Measures, Metrics, and Innovation
532
Measurements, Metrics, and Outsource Litigation
535
Measurements, Metrics, and Behavioral Changes
536
Topics Outside the Scope of Current Measurements
542
Cautions Against Simplistic and Hazardous Measures and Metrics
543
Commercial Software Measurement Tools
546
Summary and Conclusions
547
Suggested Readings on Measurement and Metrics
548
Chapter
7. Summary of Problems in Software Measurement		 549
Synthetic vs. Natural Metrics
550
Ambiguity in Defining the Nature, Scope, Class, and Type of Software
552
Ambiguity in Defining and Measuring the Activities and Tasks of Software Projects
561
False Advertising and Fraudulent Productivity Claims
564
The Absence of Project Demographic and Occupation Group Measurement
566
Ambiguity in the Span of Control and Organizational Measurements
567
The Missing Link of Measurement: When Do Projects Start?
568
Ambiguity in Measuring Milestones, Schedules, Overlap, and Schedule Slippage
568
Problems with Overlapping Activities
573
Leakage from Software Project Resource Tracking Data
573
Ambiguity in Standard Time Metrics
575
Inadequate Undergraduate and Graduate Training in Software Measurement and Metrics
578
Inadequate Standards for Software Measurement
579
Lack of Standardization of "Lines of Source Code" Metrics
580
The Hazards and Problems of Ratios and Percentages
589
Ambiguity in Measuring Development or Delivery Productivity
590
Ambiguity in Measuring Complexity
593
Ambiguity in Functional Metrics
594
Ambiguity in Quality Metrics
599
Ambiguity with the Defects per KLOC Metric
599
Ambiguity with the Cost per Defect Metric
600
Failure to Measure Defect Potentials and Defect Removal Efficiency
602
The Problems of Measuring the Impact of "Soft" Factors
603
Problems in Measuring Software Value
607
Lack of Effective Measurement and Metrics Automation
609
Social and Political Resistance to Software Measurements
617
Ambiguity in Software Measurement and Metrics Terminology
620
Failure to Use Metrics for Establishing Goals and Targets
624
Summary and Conclusions
629
Suggested Readings
630
Additional References on Software Measurements
632
Appendix. Rules for Counting Procedural Source Code 635
Project Source Code Counting Rules
637
General Rules for Counting Code Within Applications
639
Examples of the SPR Source Code Counting Rules
640
Software Productivity Research COBOL-Counting Rules
642
Index 645
McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide
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