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