The Art and Science of Analyzing Software Data
(Sprache: Englisch)
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive insight from software data. This book shares best practices in the field generated by leading data scientists, collected from their...
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Klappentext zu „The Art and Science of Analyzing Software Data “
The Art and Science of Analyzing Software Data provides valuable information on analysis techniques often used to derive 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.
Presents best practices, hints, and tips to analyze dataand apply tools in data science projectsPresents research methods and case studies that have emerged over the past few years to further understanding of software dataShares stories from the trenches of successful data science initiatives in industry
Inhaltsverzeichnis zu „The Art and Science of Analyzing Software Data “
Past, Present, and Future of Analyzing Software Data Part 1 TUTORIAL-TECHNIQUES
Mining Patterns and Violations Using Concept Analysis Analyzing Text in Software Projects Synthesizing Knowledge from Software Development Artifacts A Practical Guide to Analyzing IDE Usage Data Latent Dirichlet Allocation: Extracting Topics from Software Engineering Data Tools and Techniques for Analyzing Product and Process Data
PART 2 DATA/PROBLEM FOCUSSED
Analyzing Security Data A Mixed Methods Approach to Mining Code Review Data: Examples and a Study of Multicommit Reviews and Pull Requests Mining Android Apps for Anomalies Change Coupling Between Software Artifacts: Learning from Past Changes
PART 3 STORIES FROM THE TRENCHES
Applying Software Data Analysis in Industry Contexts: When Research Meets Reality Using Data to Make Decisions in Software Engineering:
Providing a Method to our Madness Community Data for OSS Adoption Risk Management Assessing the State of Software in a Large Enterprise: A 12-Year Retrospective Lessons Learned from Software Analytics in Practice
PART 4 ADVANCED TOPICS
Code Comment Analysis for Improving Software Quality Mining Software Logs for Goal-Driven Root Cause Analysis Analytical Product Release Planning
PART 5 DATA ANALYSIS AT SCALE (BIG DATA)
Boa: An Enabling Language and Infrastructure for Ultra-Large-Scale MSR Studies Scalable Parallelization of Specification Mining Using Distributed Computing
Autoren-Porträt von Christian Bird, Tim Menzies, Thomas Zimmermann
Bird, Christianis a researcher in the empirical software engineering group at Microsoft Research. He is primarily interested in the relationship between software design, social dynamics, and processes in large development projects. He has studied software development teams at Microsoft, IBM, and in the Open Source realm, examining the effects of distributed development, ownership policies, and the ways in which teams complete software tasks. He has published in the top Software Engineering venues and is the recipient of the ACM SIGSOFT distinguished paper award.
Bibliographische Angaben
- Autoren: Christian Bird , Tim Menzies , Thomas Zimmermann
- 2015, 672 Seiten, Maße: 19,7 x 23,7 cm, Kartoniert (TB), Englisch
- Herausgegeben:Menzies, Tim; Zimmermann, Thomas; Bird, Christian
- Herausgegeben: Tim Menzies, Thomas Zimmermann
- Verlag: Morgan Kaufmann
- ISBN-10: 0124115195
- ISBN-13: 9780124115194
- Erscheinungsdatum: 15.09.2015
Sprache:
Englisch
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