- Making Software
- Preface
- I. General Principles of Searching For and Using Evidence
- 1. The Quest for Convincing Evidence
- 2. Credibility, or Why Should I Insist on Being Convinced?
- How Evidence Turns Up in Software Engineering
- Credibility and Relevance
- Aggregating Evidence
- Types of Evidence and Their Strengths and Weaknesses
- Society, Culture, Software Engineering, and You
- Acknowledgments
- References
- 3. What We Can Learn from Systematic Reviews
- 4. Understanding Software Engineering Through Qualitative Methods
- 5. Learning Through Application: The Maturing of the QIP in the SEL
- 6. Personality, Intelligence, and Expertise: Impacts on Software Development
- 7. Why Is It So Hard to Learn to Program?
- 8. Beyond Lines of Code: Do We Need More Complexity Metrics?
- Surveying Software
- Measuring the Source Code
- A Sample Measurement
- Statistical Analysis
- Some Comments on the Statistical Methodology
- So Do We Need More Complexity Metrics?
- References
- II. Specific Topics in Software Engineering
- 9. An Automated Fault Prediction System
- 10. Architecting: How Much and When?
- Does the Cost of Fixing Software Increase over the Project Life Cycle?
- How Much Architecting Is Enough?
- Using What We Can Learn from Cost-to-Fix Data About the Value of Architecting
- So How Much Architecting Is Enough?
- Does the Architecting Need to Be Done Up Front?
- Conclusions
- References
- 11. Conway’s Corollary
- 12. How Effective Is Test-Driven Development?
- 13. Why Aren’t More Women in Computer Science?
- 14. Two Comparisons of Programming Languages
- 15. Quality Wars: Open Source Versus Proprietary Software
- 16. Code Talkers
- 17. Pair Programming
- 18. Modern Code Review
- 19. A Communal Workshop or Doors That Close?
- 20. Identifying and Managing Dependencies in Global Software Development
- 21. How Effective Is Modularization?
- 22. The Evidence for Design Patterns
- 23. Evidence-Based Failure Prediction
- 24. The Art of Collecting Bug Reports
- 25. Where Do Most Software Flaws Come From?
- 26. Novice Professionals: Recent Graduates in a First Software Engineering Job
- 27. Mining Your Own Evidence
- What Is There to Mine?
- Designing a Study
- A Mining Primer
- Where to Go from Here
- Acknowledgments
- References
- 28. Copy-Paste as a Principled Engineering Tool
- 29. How Usable Are Your APIs?
- 30. What Does 10x Mean? Measuring Variations in Programmer Productivity
- A. Contributors
- Index
- About the Authors
- Colophon
- Copyright
Some of this material is based upon the work supported by the National Science Foundation under Grants ITWF 00305917 and BPC 0540523. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation.
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