Best of Technical Debt — May 2025

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    Article
    Avatar of techworld-with-milanTech World With Milan·1y

    How Google Measures and Manages Tech Debt

    Google addresses technical debt by defining it across ten distinct categories, measuring its impact through surveys and attempted metric indicators, and managing it with strategic frameworks and tooling. A systematic approach, including debt maturity models and educational initiatives, has led to a significant reduction in productivity issues related to tech debt among Google's engineering teams. The focus is on balancing deliberate debt with ongoing remediation as part of the strategic engineering process.

  2. 2
    Article
    Avatar of infoworldInfoWorld·1y

    Technical debt is just an excuse

    Technical debt is often misused as an excuse for poor coding practices. Originally, it represented deliberate decisions to write sub-par code temporarily, with a plan to address it later. However, it has become a label for all bad code, which can stem from accidental complexity or rushed development. To reclaim its true meaning, only code with a planned fix should be labeled as technical debt. Anything else should be recognized as code rot.

  3. 3
    Article
    Avatar of devtoolsDev Tools·51w

    I made a VSCode extension to help manage Tech Debt from in your IDE

    A developer created a VSCode extension to streamline technical debt management by allowing users to create GitHub issues directly from their IDE without switching between applications. The extension automates the process of raising issues with proper labels and formatting, addressing the common workflow friction of managing tech debt across multiple tools.

  4. 4
    Article
    Avatar of thedevcraftThe Dev Craft·1y

    Why Your "Simple" Feature Became a 2,000-Line Monster

    A developer recounts how a supposedly simple feature grew into a complex and unmanageable authentication system due to over-engineering. The post discusses common pitfalls like mistaking complexity for sophistication and premature generalization, outlining the real costs such as loss of confidence among junior developers and user frustration. It suggests methods to embrace simplicity, like following the KISS principle, building modular components, and scheduling simplification sprints.

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