Prioritizing Technical Debt Using Version Control Data

Prioritizing Technical Debt Using Version Control Data

ChariotSolutions via YouTube Direct link

Tooling: Try it on your own Code

20 of 20

20 of 20

Tooling: Try it on your own Code

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Prioritizing Technical Debt Using Version Control Data

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  1. 1 Intro
  2. 2 Lehman's "Laws" of Software Evolution
  3. 3 Are We Treating Symptoms Instead of the Real Issues
  4. 4 QUANTIFYING TECHNICAL DEBT?
  5. 5 THE PERILS QUANTIFYING TECHNICAL DEBT
  6. 6 Version-Control - A Behavioral Data Source
  7. 7 Case Study: Android
  8. 8 Actionable Insights?
  9. 9 Hotspots: X-Ray ActivityManager Service. Java
  10. 10 X-Ray of ActivityManager Service.java
  11. 11 Why You Don't Have To Fix All Technical Debt
  12. 12 Code Quality In Context: Why you shouldn't fix all code is!
  13. 13 What Is Legacy Code?
  14. 14 The Technical Debt That Wasn't
  15. 15 Software Evolution power laws are everywhere
  16. 16 Case Study: Off-Boarding
  17. 17 Case Study: ASP.NET MVC Core
  18. 18 Mitigate off-boarding risks
  19. 19 There's More to Code Complexity than Code
  20. 20 Tooling: Try it on your own Code

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