This course teaches learners how to prioritize technical debt in large-scale systems, balance the trade-off between improving existing code and adding new features, and measure long-term trends in technical debt. The teaching method involves using version-control data to uncover development organization behavior and patterns, enabling informed decision-making based on data. The course is intended for software developers, engineers, and anyone involved in software development looking to improve code quality and efficiency.
Prioritizing Technical Debt as If Time and Money Matters
Overview
Syllabus
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
Taught by
GOTO Conferences
