The art and science of analyzing software data /
The art and science of analyzing software data /
[edited by] Christian Bird, Tim Menzies, Thomas Zimmermann.
- Waltham : Morgan Kaufmann / Elsevier, c.2015.
- xxiii, 660 p. : ill. ; 24 cm.
Index : p. 649-660.
Includes bibliographical references.
Access restricted by licensing agreement.
This book provides valuable information on analysis techniques often used to derive insight from software data. It shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. Topics include: analysis of security data; code reviews; app stores; log files; user telemetry; co-change, text, topic and concept analyses; release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. --
Data mining.
Quantitative research.
006.312 / ART
Index : p. 649-660.
Includes bibliographical references.
Access restricted by licensing agreement.
This book provides valuable information on analysis techniques often used to derive insight from software data. It shares best practices in the field generated by leading data scientists, collected from their experience training software engineering students and practitioners to master data science. Topics include: analysis of security data; code reviews; app stores; log files; user telemetry; co-change, text, topic and concept analyses; release planning and generation of source code comments. It includes stories from the trenches from expert data scientists illustrating how to apply data analysis in industry and open source, present results to stakeholders, and drive decisions. --
Data mining.
Quantitative research.
006.312 / ART