Software Design X-Rays (Pragmatic Bookshelf)
Monday, 05 November 2018

This book has the subtitle "Fix Technical Debt with Behavioral Code Analysis", and author Adam Tornhill aims to demonstrate novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. He shows how to use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software, then how to 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.

<ASIN:1680502727>

 

Author: Adam Tornhill
Publisher:  Pragmatic Bookshelf
Date: June 2018
Pages: 276
ISBN: 978-1680502725
Print: 1680502727
Kindle: B07BVRLZ87
Audience: Software architects and technical managers.
Level: Intermediate
Category: Methodology

 

For more Book Watch just click.

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

To have new titles included in Book Watch contact  BookWatch@i-programmer.info

Follow @bookwatchiprog on Twitter or subscribe to I Programmer's Books RSS feed for each day's new addition to Book Watch and for new reviews.

 

 

Banner
 


WordPress Plugin Development, 2nd Ed

Author: Brad Williams, Justin Tadlock, John James Jacoby
Publisher: Wrox
Pages: 480
ISBN: 978-1119666943
Print: 1119666945
Kindle: B0899MW9CP
Audience: WordPress developers
Rating: 4.5
Reviewer: Kay Ewbank

The authors of this book are well-known in the WordPress world, with more than 100 published plug [ ... ]



Machine Learning with PyTorch and Scikit-Learn

Author: Sebastian Raschka, Yuxi (Hayden) Liu & Vahid Mirjalili
Publisher: Packt
Date: February 2022
Pages: 770
ISBN: 978-1801819312
Print: 1801819319
Kindle: B09NW48MR1
Audience: Python developers interested in machine learning
Rating: 5
Reviewer: Mike James
This is a very big book of machine le [ ... ]


More Reviews