- 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
Many of the essential mining techniques described in this chapter were pioneered together with Peter Weißgerber and Thomas Zimmermann [Zimmermann et al. 2004], who deserve our eternal gratitude. Yana Mileva, Nadja Altabari, and Clemens Hammacher provided helpful comments on earlier revisions of this chapter.
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