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 |
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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 |
Open access status: | An open access version is available from UCL Discovery |
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 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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