Callan, J;
Petke, J;
(2021)
Optimising SQL Queries Using Genetic Improvement.
In:
2021 IEEE/ACM International Workshop on Genetic Improvement (GI).
IEEE
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Abstract
Structured Query Language (SQL) queries are ubiquitous in modern software engineering. These queries can be costly when run on large databases with many entries and tables to consider. We propose using Genetic Improvement (GI) to explore patches for these queries, with the aim of optimising their execution time, whilst maintaining the functionality of the program in which they are utilised. Specifically, we propose three ways in which SQL JOIN statements can be mutated in order to improve performance. We also discuss the requirements of software being improved in this manner and the potential challenges of our approach.
| Type: | Proceedings paper |
|---|---|
| Title: | Optimising SQL Queries Using Genetic Improvement |
| Event: | The 10th International Workshop on Genetic Improvement @ ICSE 2021 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/GI52543.2021.00010 |
| Publisher version: | http://doi.org/10.1109/GI52543.2021.00010 |
| 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. |
| 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/10122956 |
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