Langdon, WB;
Clark, D;
(2025)
Deep imperative mutations have less impact.
Automated Software Engineering
, 32
, Article 6. 10.1007/s10515-024-00475-4.
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Abstract
Information theory and entropy loss predict deeper more hierarchical software will be more robust. Suggesting silent errors and equivalent mutations will be more common in deeper code, highly structured code will be hard to test, so explaining best practise preference for unit testing of small methods rather than system wide analysis. Using the genetic improvement (GI) tool MAGPIE, we measure the impact of source code mutations and how this varies with execution depth in two diverse multi-level nested software. gem5 is a million line single threaded state-of-the-art C++ discrete time VLSI circuit simulator, whilst PARSEC VIPS is a non-deterministic parallel computing multi-threaded image processing benchmark written in C. More than 28–53% of mutants compile and generate identical results to the original program. We observe 12% and 16% Failed Disruption Propagation (FDP). Excluding internal errors, exceptions and asserts, here most faults below about 30 nested function levels which are Executed and Infect data or divert control flow are not Propagated to the output, i.e. these deep PIE changes have no visible external effect. Suggesting automatic software engineering on highly structured code will be hard.
| Type: | Article |
|---|---|
| Title: | Deep imperative mutations have less impact |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s10515-024-00475-4 |
| Publisher version: | https://doi.org/10.1007/s10515-024-00475-4 |
| Language: | English |
| Additional information: | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
| Keywords: | Automatic code optimisation · Failed disruption propagation (FDP), Genetic improvement (GI), Fault masking, Software resilience, Fitness landscape |
| 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-pp.ucl.ac.uk/id/eprint/10202703 |
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