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Software Design X-Rays: Fix Technical Debt with Behavioral Code Analysis 1st Edition

by Adam Tornhill (Author)

4.4 55 ratings

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Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code!

Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions.

In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards 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.

What You Need:

You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.

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The Pragmatic Programmers publishes hands-on, practical books on classic and cutting-edge software development and engineering management topics. We help professionals solve real-world problems, hone their skills, and advance their careers.
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About the Author

Adam Tornhill is a programmer who combines degrees in engineering and psychology. He's the founder of Empear, where he designs tools for software analysis. Adam is the author of Your Code as a Crime Scene, Lisp for the Web, and Patterns in C. His other interests include modern history, music, and martial arts.

Product details

Publisher ‏ : ‎ Pragmatic Bookshelf; 1st edition (April 17, 2018)
Language ‏ : ‎ English
Paperback ‏ : ‎ 276 pages
ISBN-10 ‏ : ‎ 1680502727
ISBN-13 ‏ : ‎ 978-1680502725
Item Weight ‏ : ‎ 1.14 pounds
Dimensions ‏ : ‎ 7.5 x 0.58 x 9.25 inches

Best Sellers Rank: #944,437 in Books (See Top 100 in Books)
- #200 in Computer Hardware Design & Architecture
- #947 in Microsoft Programming (Books)
- #2,182 in Software Design, Testing & Engineering (Books)

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4.4 55 ratings

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Reviewed in France on August 6, 2020

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Quand on est développeur et qu'on lit des livres techniques, on est content quand on en a pour son argent avec de bons livres qui vous font progresser mais une fois de temps en temps on tombe sur quelque chose qui change totalement sa manière de travailler. Ce livre est dans la seconde catégorie.
On part pourtant d'un constat de base simple : le fonctionnement de Git (ou autre SCV peu importe) fait que vous avez à votre disposition tout l'historique du projet, d'où la question "que peut-on tirer de cette mine d'informations ?" Et bien énormément, ce que l'auteur nous démontre au fil du livre, en se basant sur l'analyse de véritables projets open-source.
Quand on parle de dette technique, ce qui limite l'utilité de la métaphore, c'est qu'on se heurte vite au problème du manque de données. Ce qui fait de ce livre de loin le meilleur que j'ai lu sur ce sujet, c'est qu'il est le plus concret : aborder une codebase inconnue, trouver les problèmes, les prioriser, les rendre tangibles pour les stakeholders, complèter les outils d'analyse statique qui ne peuvent pas prendre en compte l'aspect "legacy" et vous annonce des 40ans/homme de problèmes à résoudre, diagnostiquer les problèmes de bottlenecks entre équipes, etc.
Le tout basé non pas sur des approximations ou des impressions mais des données concrètes et vérifiables.
Anecdote: j'ai pu trouver un bug dans du code inconnu d'une autre équipe juste grâce à l'analyse coupling/duplication.
Bref change complètement la donne quand on parle de dette technique, à recommander à tout professionnel.
À noter que le code utilisé dans le livre est sur Github donc on peut aussi jouer avec.