Prioritizing Technical Debt as If Time and Money Matters

Explore strategies for prioritizing technical debt in large-scale software systems through this insightful conference talk. Learn how to balance improving existing code with adding new features, and discover techniques for measuring long-term trends in technical debt. Delve into real-world case studies from codebases like Android, Linux Kernel, and .Net Core Runtime to gain a new perspective on software development. Uncover methods to mine version-control data for insights into development organization behavior and patterns. Gain practical knowledge on measuring code complexity, understanding the relationship between technical debt and people, and assessing how quickly a codebase can become legacy. Leave with actionable approaches to make informed decisions about code improvements and maintain a healthy balance between short-term and long-term development goals.

Intro
Lehman's "laws" of software evolution
Technical debt
Case study: Prioritizing technical debt
Can we measure "code complexity"?
Technical debt & people
Case study: How quickly can you turn your current codebase into legacy code?
Resources