A success story in applying data science in practice

A. Bener, B. Turhan, A. Tosun, B. Caglayan, E. Kocaguneli

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


In software engineering, the primary objective is delivering high-quality systems within budget and time constraints. Managers struggle to make many decisions under a lot of uncertainty. They would like to be confident in the product, team, and the processes. Therefore, the need for evidence-based decision making, a.k.a. data science and analysis, has been growing in the software development industry as data becomes available. Data science involves analytics for using data to understand the past and present, to analyze past performance, and for using optimization and/or prediction techniques.

Original languageEnglish
Title of host publicationPerspectives on Data Science for Software Engineering
Number of pages6
ISBN (Electronic)9780128042069
ISBN (Print)9780128042618
Publication statusPublished - 1 Jan 2016

Bibliographical note

Publisher Copyright:
© 2016 Elsevier Inc. All rights reserved.


  • Confidence factor modeling
  • Data collection
  • Data science
  • Learning-based predictive models
  • Measurement and data extraction tool
  • Model selection
  • Problem selection
  • Tool support


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