Arch. App: Prioritizing Technical Debt as if Time and Money Matters
summary
Claims version-control data reveals where to spend effort, using a hotspot analysis that flags high-change, large modules and a hotspot x-ray that drills to function level. Example: Android platform framework base ~3M LOC, an ActivityManager file ~20k LOC touched by 74 developers in three months; a handleMessage function ~500 LOC, changed 96 times last year, cyclomatic complexity ~106. Tools: plain git (git log -L) and CodeScene (codexin.io). Results guide focused refactors that are mergeable and reduce real risk.
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chapters (10)
- 0:00Introduction to technical debt
- 3:21Why quantifying debt fails
- 8:15Hotspot analysis explained
- 16:14Power law in code evolution
- 20:30Legacy code vs technical debt
- 23:21Social factors in code complexity
- 26:30Tools for behavioral analysis
- 28:16Microservices and hotspots
- 31:50Change coupling in microservices
- 36:48Summary and next steps
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