
Evidence-based Software Engineering
Derek M. Jones
Copyright Year:
ISBN 13: 9781838291303
Publisher: Knowledge Software
Language: English
Formats Available
Conditions of Use
Attribution-ShareAlike
CC BY-SA
Reviews





The book covers the data that is publicly available on building and maintaining software systems. The book is comprehensive in the sense that it systematically covers that available data. The book is not comprehensive in the sense that for some... read more
Reviewed by Christoph Csallner, Professor, University of Texas at Arlington on 5/22/24
Comprehensiveness
The book covers the data that is publicly available on building and maintaining software systems. The book is comprehensive in the sense that it systematically covers that available data. The book is not comprehensive in the sense that for some areas of software development there is little to no publicly available data. While other books may then instead report on private data, this book just omits such software development areas.
Content Accuracy
The book is very accurate in the sense that the book's author also provides the underlying data and code. This allows readers to study the data and redo the data analysis. Specifically, the book's author maintains a public repository of the software engineering data the book discusses (in addition to the book author's own code for analyzing and visualizing that data) as a public GitHub repository (https://github.com/Derek-Jones/ESEUR-code-data).
Relevance/Longevity
The book is up to date and the book's author has posted updates to the book's GitHub repository (https://github.com/Derek-Jones/ESEUR-code-data).
Clarity
The writing is clear and tight. There is little (if any) fluff.
Consistency
The writing is consistent.
Modularity
The text is highly modular. Each section is broken into sub-sections and sub-sub-sections with their own descriptive titles. Paragraphs are compact and focused on the relevant point.
Organization/Structure/Flow
The book's sections make sense.
Interface
Text and figures are well laid out and are easy to read.
Grammatical Errors
The text is well edited.
Cultural Relevance
The book focuses on publicly available software development data and thus avoids the made-up worked examples commonly found in traditional textbooks.
CommentsI wish every book would provide this level of access to the data underlying the book.
Table of Contents
- 1 Introduction
- 2 Human cognition
- 3 Cognitive capitalism
- 4 Ecosystems
- 5 Projects
- 6 Reliability
- 7 Source code
- 8 Stories told by data
- 9 Probability
- 10 Statistics
- 11 Regression modeling
- 12 Miscellaneous techniques
- 13 Experiments
- 14 Data preparation
- 15 Overview of R
About the Book
This book discusses what is currently known about software engineering, based on an analysis of all the publicly available data. This aim is not as ambitious as it sounds, because there is not a great deal of data publicly available.
The intent is to provide material that is useful to professional developers working in industry; until recently researchers in software engineering have been more interested in vanity work, promoted by ego and bluster.
The material is organized in two parts, the first covering software engineering and the second the statistics likely to be needed for the analysis of software engineering data.
About the Contributors
Author
Derek M. Jones