Edited by Adaobi Obi Tulton @aotulton
Battle cost overruns, death marches, and legacy code monsters with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. Statistics and data science can uncover problematic code and the behaviors of developers, giving insights you can’t get from the code alone. Use these insights to gauge refactoring needs, measure their effect, find implicit dependencies, and create knowledge maps of your system based on code contributions.
Learn to guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover language-neutral practical analysis techniques based on version-control data, with case studies from real-world codebases. Apply research findings from social psychology to software development, and coach your organization toward better code.
If you’re an experienced programmer, software architect, or technical manager, you’ll get a new perspective that will change how you work with code.
"Adam takes you behind the scenes of pragmatic software analysis. He’s bridging the gap between algorithms for mining software repositories and performing refactorings based on the gained insights."
–Markus Harrer, Software Development Analyst
- Full details: https://pragprog.com/book/atevol/software-design-x-rays
- View this book’s portal and details on how to post errata and suggestions here.
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