If it is software engineering, it is (probably) a Bayesian factor

A. Bener, A. Tosun

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

1 Citation (Scopus)


For more than two decades, we have witnessed how software is developed in the industry and later conducted empirical research in academia to build predictive models, mine software repositories, and perform various software analytics tasks to help software development teams make evidence-based decisions.

Original languageEnglish
Title of host publicationPerspectives on Data Science for Software Engineering
Number of pages5
ISBN (Electronic)9780128042069
ISBN (Print)9780128042618
Publication statusPublished - 1 Jan 2016

Bibliographical note

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


  • Artificial intelligence (AI)
  • Bayesian Networks (BN)
  • Causal relationships
  • Gibbs sampling
  • Hybrid Bayesian Network


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