Technical Debt in Practice: How to Find It and Fix It

Ernst, Neil,Kazman, Rick,Delange, Julien

ISBN 10: 0262542110 / ISBN 13: 9780262542111

Published by The MIT Press, 2021

About this Item

Very Good Condition - May show some limited signs of wear and may have a remainder mark. Pages and dust cover are intact and not marred by notes or highlighting.

Seller Inventory # MIT-PB-VG-0262542110

Bibliographic Details

• Title: Technical Debt in Practice: How to Find It and Fix It
• Publisher: The MIT Press
• Publication Date: 2021
• Language: English
• ISBN 10: 0262542110
• ISBN 13: 9780262542111
• Binding: paperback
• Condition: Very Good

About this title

Synopsis

The practical implications of technical debt for the entire software lifecycle; with examples and case studies.

Technical debt in software is incurred when developers take shortcuts and make ill-advised technical decisions in the initial phases of a project, only to be confronted with the need for costly and labor-intensive workarounds later. This book offers advice on how to avoid technical debt, how to locate its sources, and how to remove it. It focuses on the practical implications of technical debt for the entire software life cycle, with examples and case studies from companies that range from Boeing to Twitter.

Technical debt is normal; it is part of most iterative development processes. But if debt is ignored, over time it may become unmanageably complex, requiring developers to spend all of their effort fixing bugs, with no time to add new features--and after all, new features are what customers really value. The authors explain how to monitor technical debt, how to measure it, and how and when to pay it down. Broadening the conventional definition of technical debt, they cover requirements debt, implementation debt, testing debt, architecture debt, documentation debt, deployment debt, and social debt. They intersperse technical discussions with "Voice of the Practitioner" sidebars that detail real-world experiences with a variety of technical debt issues.

About the Author

Neil Ernst is Assistant Professor of Computer Science at the University of Victoria, British Columbia. Julien Delange is Staff Software Engineer at Twitter and Founder of Code Inspector, a technical debt platform analysis. Rick Kazman is Professor in the Department of Information Technology Management at the University of Hawaii and Visiting Researcher at the Software Engineering Institute at Carnegie Mellon University.