The Art and Science of Analyzing Software Data

Nonfiction, Computers, Database Management, Data Processing, Programming, Software Development, General Computing
Cover of the book The Art and Science of Analyzing Software Data by , Elsevier Science
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9780124115439
Publisher: Elsevier Science Publication: September 2, 2015
Imprint: Morgan Kaufmann Language: English
Author:
ISBN: 9780124115439
Publisher: Elsevier Science
Publication: September 2, 2015
Imprint: Morgan Kaufmann
Language: English

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 data and apply tools in data science projects
  • Presents research methods and case studies that have emerged over the past few years to further understanding of software data
  • Shares stories from the trenches of successful data science initiatives in industry
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Elsevier Science

Cover of the book Advances in Experimental Social Psychology by
Cover of the book Advances in Applied Microbiology by
Cover of the book The HDL Handbook by
Cover of the book Advances in Botanical Research by
Cover of the book Construction Hazardous Materials Compliance Guide by
Cover of the book Contemporary Financial Intermediation by
Cover of the book DNA Structure and Function by
Cover of the book Machine Learning: Theory and Applications by
Cover of the book The Science of Algorithmic Trading and Portfolio Management by
Cover of the book Petroleum Rock Mechanics by
Cover of the book Multi-Camera Networks by
Cover of the book The Best Damn Exchange, SQL and IIS Book Period by
Cover of the book Sedimentary Basins and Petroleum Geology of the Middle East by
Cover of the book Binary Polar Liquids by
Cover of the book Trading and Money Management in a Student-Managed Portfolio by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy