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Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone?

Sarro, F; (2019) Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone? In: Nejati, S and Gay, G, (eds.) Search-Based Software Engineering: 11th International Symposium, SSBSE 2019, Tallinn, Estonia, August 31 – September 1, 2019, Proceedings. (pp. pp. 3-7). Springer: Cham, Switzerland.

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Abstract

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.Predictive analytics Predictive modelling Search-based software engineering Machine learning Software analytics

Type: Proceedings paper
Title: Search-Based Predictive Modelling for Software Engineering: How Far Have We Gone?
Event: 2019 International Symposium on Search Based Software Engineering (SSBSE 2019)
ISBN-13: 9783030274542
DOI: 10.1007/978-3-030-27455-9_1
Publisher version: https://doi.org/10.1007/978-3-030-27455-9_1
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Predictive analytics, Predictive modelling, Search-based software engineering, Machine learning, Software analytics
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10084775
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