The art and science of analyzing software data / edited by Christian Bird, Microsoft Research, Redmont, WA, USA, Tim Menzies, North Carolina State University, Raleigh, NC, USA, Thomas Zimmermann, Microsoft Research, Redmond, WA, USA

Contributor(s):

Massachusetts : Morgan Kaufmann is an imprint of Elsevier, c2015Description: xxiii, 660 pages ; 24 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9780124115194

Subject(s):

Data mining

DDC classification:

006.312 .B618 2015

Summary: "The Art and Science of Analyzing Software Data - a comprehensive guide to the art and science of analyzing software data, with best practices generated by leading data scientists, collected from their experience training software engineering students and practitioners on how to masters data science. It also provides information on analysis techniques often used to deeive insight from software data. This book 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. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as 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." -- Publisher's description.

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
Print Materials	Main Library General Circulation	006.312 .B618 2015 (Browse shelf(Opens below))	Available		0117808

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Previous	006.31 .F981 2018 Fundamentals of machine learning /	006.31 .M697 2017 Machine learning :	006.31 .R729 2017 A first course in machine learning /	006.312 .B618 2015 The art and science of analyzing software data /	006.312 .D232 2017 Data mining /	006.312 .Ig24 2018 An introduction to text mining :	006.312 .L783 2016 Computational and statistical methods for analysing big data with applications /	Next

Includes bibliographical references (pages 646-648) and index.

"The Art and Science of Analyzing Software Data - a comprehensive guide to the art and science of analyzing software data, with best practices generated by leading data scientists, collected from their experience training software engineering students and practitioners on how to masters data science. It also provides information on analysis techniques often used to deeive insight from software data. This book 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. The book covers topics such as the analysis of security data, code reviews, app stores, log files, and user telemetry, among others. It covers a wide variety of techniques such as co-change analysis, text analysis, topic analysis, and concept analysis, as well as advanced topics such as 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." -- Publisher's description.

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Text in English

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