Optimising SQL Queries Using Genetic Improvement (GI 2021)

Who

James Callan, Justyna Petke

Track

GI 2021

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When

Sun 30 May 2021 19:50 - 20:00 at GI Room - Session 1

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.

Link to Preprint

https://geneticimprovementofsoftware.com/paper_pdfs/gi2021icse/callan_gi-icse_2021.pdf

James Callan

UCL

Justyna Petke

University College London

United Kingdom

YT Video

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Session Program

Sun 30 May
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19:25 - 21:10	Session 1GI 2021 at GI Room

19:25 25m Long-paper		Uniform Edit Selection for Genetic Improvement: Empirical Analysis of Mutation Operator Efficacy GI 2021 Marta Smigielska University College London, Aymeric Blot University College London, Justyna Petke University College London Pre-print Media Attached
19:50 10m Short-paper		Optimising SQL Queries Using Genetic Improvement GI 2021 James Callan UCL, Justyna Petke University College London Pre-print Media Attached
20:00 25m Long-paper		Exploring the Accuracy - Energy Trade-off in Machine Learning GI 2021 Alexander E.I. Brownlee University of Stirling, Jason Adair University of Stirling, Saemundur O. Haraldsson University of Stirling, John Jabbo University of Stirling Pre-print Media Attached
20:25 10m Short-paper		Open Challenges in Genetic Improvement for Emergent Software Systems GI 2021 Penelope Faulkner Rainford Lancaster University, Barry Porter Lancaster University Pre-print Media Attached
20:35 25m Long-paper		Using Genetic Improvement to Retarget Quantum Software on Differing Hardware GI 2021 George O'Brien University of Sheffield, John Clark University of Sheffield Media Attached
21:00 10m Short-paper		(Genetically) Improving Novelty in Procedural Story Generation GI 2021 Erik Fredericks Grand Valley State University, Byron Devries Grand Valley State University Pre-print Media Attached

Information for Participants

Sun 30 May 2021 19:25 - 21:10 at GI Room - Session 1

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