Technical Debt Management & Code Quality Governance
Technical debt isn't just a synonym for "bad code" — it's an explicit trade-off between delivery speed and long-term code health that you can and should manage. That means classifying debt (deliberate vs. accidental, prudent vs. reckless), using automated quality gates (tests, linters, formatters, static analysis, coverage or mutation thresholds in CI), and applying governance mechanisms such as review policies, a Definition of Done, and deprecation policies.
Starting Points
- Winters, T., Manshreck, T., & Wright, H. (2020). Software Engineering at Google: Lessons Learned from Programming Over Time. O'Reilly.
- Martin, R. C. (2025). Clean Code: A Handbook of Agile Software Craftsmanship (2nd ed.). Prentice Hall.
- Kruchten, P., Nord, R. L., & Ozkaya, I. (2012). "Technical Debt: From Metaphor to Theory and Practice." IEEE Software.
Key Points
- You identify and categorise different forms of technical debt in an existing codebase and explain their impact on maintainability, reliability, and delivery speed.
- You apply practices such as style guides, code review checklists, and clear ownership to keep changes understandable and consistent.
- You design or improve a basic quality governance setup: automated checks (tests, linters, formatters, static analysis, coverage/mutation thresholds) configured as CI quality gates.
- You propose a realistic technical debt management plan: how to log debt items, estimate impact, prioritise remediation, and schedule refactoring alongside feature work.
- You communicate the trade-offs of incurring and paying down technical debt to non-technical stakeholders, using concrete risks and benefits.
- You demonstrate, in a project or case study, at least one instance of paying down technical debt and explain the rationale and observed benefit.