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Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e

Guizzo, G; Blot, A; Callan, J; Petke, J; Sarro, F; (2021) Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e. In: Sarro, F and Deb, K, (eds.) SSBSE: International Symposium on Search Based Software Engineering. Springer: Cham, Switzerland. Green open access

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Abstract

Several tools support code templates as a means to specify searches within a program’s source code. Despite their ubiquity, code templates can often prove difficult to specify, and may produce too many or too few match results. In this paper, we present a search-based approach to support developers in specifying templates. This approach uses a suite of mutation operators to recommend changes to a given template, such that it matches with a desired set of code snippets. We evaluate our approach on the problem of inferring a code template that matches all instances of a design pattern, given one instance as a starting template.

Type: Proceedings paper
Title: Refining Fitness Functions for Search-Based Automated Program Repair: A Case Study with ARJA and ARJA-e
Event: Search-Based Software Engineering (SSBSE)
Location: Bari, Italy
Dates: 11 October 2021 - 15 October 2021
Open access status: An open access version is available from UCL Discovery
DOI: 10.1007/978-3-319-47106-8_13
Publisher version: https://doi.org/10.1007/978-3-319-47106-8_13
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: Templates, Evolutionary algorithms, Recommender systems
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/10131848
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