TY  - GEN
Y1  - 2021/07/07/
AV  - public
TI  - Optimising SQL Queries Using Genetic Improvement
N1  - This version is the author accepted manuscript. For information on re-use, please refer to the publisher?s terms and conditions.
UR  - http://doi.org/10.1109/GI52543.2021.00010
PB  - IEEE
N2  - 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.
ID  - discovery10122956
A1  - Callan, J
A1  - Petke, J
ER  -