Feb 23 2025 Goodhart's Law in Software Engineering

• Definition of Goodhart's Law: When a measure becomes a target, it ceases to be a good measure.
• Weak Interpretation: Metrics can be manipulated, leading to practices like closing bugs without proper resolution to reduce bug counts.
• Strong Interpretation: Even with honest intentions, overemphasis on specific metrics can detract from actual goals due to the inherent difference between metrics and true objectives.
• Example in Software Reliability: Using the number of open bugs as a proxy for software reliability can be misleading, as it doesn't account for unreported issues or the quality of fixes.
• Biological Analogy: Peacock tail evolution demonstrates Goodhart's Law; extravagant tails, initially a fitness indicator, can become detrimental when overemphasized.
• Engineering Metrics Affected:
• Test Coverage: May not reflect the depth or effectiveness of tests.
• Cyclomatic Complexity and Function Size: Focusing solely on these can overlook overall code readability and maintainability.
• Benchmarks: Optimizing for specific benchmarks might degrade performance in unmeasured areas.
• Challenges in Mitigation: Balancing multiple metrics to avoid overoptimization is complex and may lead to conflicting priorities.

The full post is available here.