Monash University
Thesis-Anjana Perera.pdf (2.33 MB)

Using Defect Prediction to Improve the Bug Detection Capability of Search-Based Software Testing

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posted on 2022-09-30, 05:02 authored by BALASURIYAGE ANJANA VISULA PERERA
Software systems have a direct and indirect impact on the lives of humans, animals and other living things. They need to be tested thoroughly to minimise software failures. Automated test generators, like search-based software testing (SBST) techniques, replace the tedious and expensive task of manually writing tests. Despite achieving high code coverage, current SBST techniques perform rather poorly in terms of detecting bugs. This thesis proposes novel SBST approaches guided by defect prediction and demonstrates that to effectively and efficiently detect bugs SBST needs to focus test generation more on likely buggy areas in programs guided by defect prediction.


Campus location


Principal supervisor

Aldeida Aleti

Additional supervisor 1

Marcel Boehme

Additional supervisor 2

Burak Turhan

Year of Award


Department, School or Centre

Software Systems & Cybersecurity


Doctor of Philosophy

Degree Type



Faculty of Information Technology