Many applications are developed with a lot of di↵erent purposes and can provide quality output.
Nevertheless, crashes still happen. Many techniques such as unit testing, peer-reviewing, or crash
reproduction are being researched to improve quality by reducing crashes. This thesis contributes to
the fast evolving field of research on crash reproduction tools. These tools seek better reproduction
with minimum information as input while delivering correct outputs in various scenarios. Di↵erent
approaches have previously been tested to gather input-output data, also called benchmarks, but
they often take time and manual e↵ort to be usable. The research documented in this thesis
endeavours to synthesize crashes using mutation testing to serve as input for crash reproduction
tools.
Date of Award | 17 Jun 2022 |
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Original language | English |
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Awarding Institution | |
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Supervisor | Xavier Devroey (Supervisor) |
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Towards crash reproduction benchmark augmentation using mutation testing
AU, T. (Author). 17 Jun 2022
Student thesis: Master types › Master in Computer science