Langdon, William B;
Clark, David;
(2024)
Deep Mutations have Little Impact.
In:
GI '24: Proceedings of the 13th ACM/IEEE International Workshop on Genetic Improvement.
(pp. pp. 1-8).
ACM (Association for Computing Machinery): New York, NY, USA.
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Abstract
Using MAGPIE (Machine Automated General Performance Improvement via Evolution of software), we measure the impact of genetic improvement (GI) on a non-deterministic deeply nested PARSEC VIPS parallel computing multi-threaded image processing benchmark written in C. More than 53% of mutants compile and generate identical results to the original program. We find about 10% Failed Disruption Propagation (FDP). Excluding internal errors and asserts, almost all changes deeper than 30 nested functions which are Executed and Infect data or change control are not Propagated to the output, i.e. these deep PIE changes have no external effect. Suggesting (where it relies on testing) automatic software engineering on deeply nested code will be hard.
| Type: | Proceedings paper |
|---|---|
| Title: | Deep Mutations have Little Impact |
| Event: | GI '24: 13th ACM/IEEE International Workshop on Genetic Improvement |
| ISBN-13: | 979-8-4007-0573-1 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3643692.3648259 |
| Publisher version: | http://dx.doi.org/10.1145/3643692.3648259 |
| Language: | English |
| Additional information: | This work is licensed under a Creative Commons Attribution-NoDerivs International 4.0 License, https://creativecommons.org/licenses/by-nd/4.0/deed.en. |
| Keywords: | Software testing, robust software, fault masking, resilience, repair, automatic code optimisation, failed disruption propagation, FDP, PIE (propagation, infection, and execution), fitness landscape, information theory, genetic programming, local search, SBSE |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10195944 |
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