Table of Contents for
Your Code as a Crime Scene

Version ebook / Retour

Cover image for bash Cookbook, 2nd Edition Your Code as a Crime Scene by Adam Tornhill Published by Pragmatic Bookshelf, 2015
  1. Title Page
  2. Your Code as a Crime Scene
  3. Your Code as a Crime Scene
  4. For the Best Reading Experience...
  5. Table of Contents
  6. Early praise for Your Code as a Crime Scene
  7. Foreword by Michael Feathers
  8. Acknowledgments
  9. Chapter 1: Welcome!
  10. About This Book
  11. Optimize for Understanding
  12. How to Read This Book
  13. Toward a New Approach
  14. Get Your Investigative Tools
  15. Part 1: Evolving Software
  16. Chapter 2: Code as a Crime Scene
  17. Meet the Problems of Scale
  18. Get a Crash Course in Offender Profiling
  19. Profiling the Ripper
  20. Apply Geographical Offender Profiling to Code
  21. Learn from the Spatial Movement of Programmers
  22. Find Your Own Hotspots
  23. Chapter 3: Creating an Offender Profile
  24. Mining Evolutionary Data
  25. Automated Mining with Code Maat
  26. Add the Complexity Dimension
  27. Merge Complexity and Effort
  28. Limitations of the Hotspot Criteria
  29. Use Hotspots as a Guide
  30. Dig Deeper
  31. Chapter 4: Analyze Hotspots in Large-Scale Systems
  32. Analyze a Large Codebase
  33. Visualize Hotspots
  34. Explore the Visualization
  35. Study the Distribution of Hotspots
  36. Differentiate Between True Problems and False Positives
  37. Chapter 5: Judge Hotspots with the Power of Names
  38. Know the Cognitive Advantages of Good Names
  39. Investigate a Hotspot by Its Name
  40. Understand the Limitations of Heuristics
  41. Chapter 6: Calculate Complexity Trends from Your Code’s Shape
  42. Complexity by the Visual Shape of Programs
  43. Learn About the Negative Space in Code
  44. Analyze Complexity Trends in Hotspots
  45. Evaluate the Growth Patterns
  46. From Individual Hotspots to Architectures
  47. Part 2: Dissect Your Architecture
  48. Chapter 7: Treat Your Code As a Cooperative Witness
  49. Know How Your Brain Deceives You
  50. Learn the Modus Operandi of a Code Change
  51. Use Temporal Coupling to Reduce Bias
  52. Prepare to Analyze Temporal Coupling
  53. Chapter 8: Detect Architectural Decay
  54. Support Your Redesigns with Data
  55. Analyze Temporal Coupling
  56. Catch Architectural Decay
  57. React to Structural Trends
  58. Scale to System Architectures
  59. Chapter 9: Build a Safety Net for Your Architecture
  60. Know What’s in an Architecture
  61. Analyze the Evolution on a System Level
  62. Differentiate Between the Level of Tests
  63. Create a Safety Net for Your Automated Tests
  64. Know the Costs of Automation Gone Wrong
  65. Chapter 10: Use Beauty as a Guiding Principle
  66. Learn Why Attractiveness Matters
  67. Write Beautiful Code
  68. Avoid Surprises in Your Architecture
  69. Analyze Layered Architectures
  70. Find Surprising Change Patterns
  71. Expand Your Analyses
  72. Part 3: Master the Social Aspects of Code
  73. Chapter 11: Norms, Groups, and False Serial Killers
  74. Learn Why the Right People Don’t Speak Up
  75. Understand Pluralistic Ignorance
  76. Witness Groupthink in Action
  77. Discover Your Team’s Modus Operandi
  78. Mine Organizational Metrics from Code
  79. Chapter 12: Discover Organizational Metrics in Your Codebase
  80. Let’s Work in the Communication Business
  81. Find the Social Problems of Scale
  82. Measure Temporal Coupling over Organizational Boundaries
  83. Evaluate Communication Costs
  84. Take It Step by Step
  85. Chapter 13: Build a Knowledge Map of Your System
  86. Know Your Knowledge Distribution
  87. Grow Your Mental Maps
  88. Investigate Knowledge in the Scala Repository
  89. Visualize Knowledge Loss
  90. Get More Details with Code Churn
  91. Chapter 14: Dive Deeper with Code Churn
  92. Cure the Disease, Not the Symptoms
  93. Discover Your Process Loss from Code
  94. Investigate the Disposal Sites of Killers and Code
  95. Predict Defects
  96. Time to Move On
  97. Chapter 15: Toward the Future
  98. Let Your Questions Guide Your Analysis
  99. Take Other Approaches
  100. Let’s Look into the Future
  101. Write to Evolve
  102. Appendix 1: Refactoring Hotspots
  103. Refactor Guided by Names
  104. Bibliography
  105. You May Be Interested In…

Understand Pluralistic Ignorance

What just happened in our fictional example is that you fell prey to pluralistic ignorance. Pluralistic ignorance happens in situations where everyone privately rejects a norm but thinks that everyone else in the group supports it. Over time, pluralistic ignorance can lead to situations where a group follows rules that all of its members reject in private.

We fall in this social trap when we conclude that the behavior of our peers depends on beliefs that are different from our own, even if we behave in an identical way ourselves. That’s what happened around Andersen’s naked emperor. Because everyone praised the emperor’s new clothes, each individual thought they missed something obvious. That’s why they chose to conform to the group behavior and play along with the praise of the wonderful clothes they couldn’t see.

images/Emperor_Clothes_Full_Size.jpg

Another common social bias is to mistake a familiar opinion for a widespread one. If we hear the same option repeatedly, we come to think of that opinion as more prevalent than it really is. As if that wasn’t bad enough, we fall for the bias even if it’s the same person who keeps expressing that opinion (source: Inferring the popularity of an opinion from its familiarity: A repetitive voice can sound like a chorus [WMGS07]).

This means it’s enough with one individual, constantly expressing a strong opinion, to bias your whole software development project. It may be about technology choices, methodologies, or programming languages. Let’s see what you can do about it.

Challenge with Questions and Data

Most people don’t like to express deviating opinions, but there are exceptions. One case is when our minority opinion is aligned with the group ideal. That is, we have a minority opinion, but it deviates from the group norm in a positive way; the group has some quality it values, and we take a more extreme position and value it even more. In that setting, we’re more inclined to speak up, and we’ll feel good about it when we do.

Within our world of programming, such “good” minority opinions may include desired attributes such as automatic tests and code quality. For example, if tests are good, then testing everything must be even better (even if it forces us to slice our designs in unfathomable pieces). And since code quality matters, we must write code of the highest possible quality all the time (even when prototyping throwaway code).

Given what we know about pluralistic ignorance and our tendency to mistake familiar opinions for common ones, it’s easy to see how these strong, deviating opinions may move a team in a more extreme direction.

Social biases are hard to avoid. When you suspect them in your team, try one of the following approaches:

  • Ask questions: By asking a question, you make others aware that the proposed views aren’t shared by everyone.

  • Talk to people: Decision biases like pluralistic ignorance often grow from our fears of rejection and criticism. So if you think a decision is wrong but everyone else seems fine with it, talk to your peers. Ask them what they like about the decision.

  • Support decisions with data: We cannot avoid social and cognitive biases. What we can do is to check our assumptions with data that either supports or challenges the decision. The rest of this book will arm you with several analyses for this purpose.

If you’re in a leadership position, you have additional possibilities to guide your group toward good decisions:

  • Use outside experts to review your decisions.

  • Let subgroups work independently on the same problem.

  • Avoid advocating a specific solution early in the discussions.

  • Discuss worst-case scenarios to make the group risk-aware.

  • Plan a second meeting upfront to reconsider the decisions of the first one.

These strategies are useful to avoid groupthink (source: Group Process, Group Decision, Group Action [BK03]). Groupthink is a disastrous consequence of social biases where the group ends up supressing all forms of internal dissent. The result is group decisions that ignore alternatives and the risk of failure, and that give a false sense of consensus.

As you’ve seen, pluralistic ignorance often leads to groupthink. This seems to be what happened in the Thomas Quick case.