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Publication Detail
Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone?
  • Publication Type:
    Conference
  • Authors:
    Sarro F
  • Publisher:
    Springer
  • Publication date:
    01/09/2019
  • Pagination:
    3, 7
  • Published proceedings:
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Volume:
    11664 LNCS
  • ISBN-13:
    9783030274542
  • Status:
    Published
  • Name of conference:
    SSBSE 2019 - International Symposium on Search Based Software Engineering
  • Conference place:
    Tallinn, Estonia
  • Conference start date:
    31/08/2019
  • Conference finish date:
    01/09/2019
  • Print ISSN:
    0302-9743
Abstract
© Springer Nature Switzerland AG 2019. In this keynote I introduce the use of Predictive Analytics for Software Engineering (SE) and then focus on the use of search-based heuristics to tackle long-standing SE prediction problems including (but not limited to) software development effort estimation and software defect prediction. I review recent research in Search-Based Predictive Modelling for SE in order to assess the maturity of the field and point out promising research directions. I conclude my keynote by discussing best practices for a rigorous and realistic empirical evaluation of search-based predictive models, a condicio sine qua non to facilitate the adoption of prediction models in software industry practices.
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