Callan, James;
Petke, Justyna;
(2025)
Multi-Objective Improvement of Android Applications.
Automated Software Engineering
, 32
(2)
pp. 1-36.
10.1007/s10515-024-00472-7.
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Abstract
Non-functional properties, such as runtime or memory use, are important to mobile app users and developers, as they affect user experience. We propose a practical approach and the first open-source tool, GIDroid for multi-objective automated improvement of Android apps. In particular, we use Genetic Improvement, a search-based technique that navigates the space of software variants to find improved software. We use a simulation-based testing framework to greatly improve the speed of search. GIDroid contains three state-of-the-art multi-objective algorithms, and two new mutation operators, which cache the results of method calls. Genetic Improvement relies on testing to validate patches. Previous work showed that tests in open-source Android applications are scarce. We thus wrote tests for 21 versions of 7 Android apps, creating a new benchmark for performance improvements. We used GIDroid to improve versions of mobile apps where developers had previously found improvements to runtime, memory, and bandwidth use. Our technique automatically re-discovers 64% of existing improvements. We then applied our approach to current versions of software in which there were no known improvements. We were able to improve execution time by up to 35%, and memory use by up to 33% in these apps.
| Type: | Article |
|---|---|
| Title: | Multi-Objective Improvement of Android Applications |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1007/s10515-024-00472-7 |
| Publisher version: | https://doi.org/10.1007/s10515-024-00472-7 |
| 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: | Android Apps, Genetic Improvement, Multi-Objective Optimization, Search-Based Software Engineering |
| 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/10198292 |
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