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Communication Dans Un Congrès Année : 2019

PyGGI 2.0: language independent genetic improvement framework

Aymeric Blot
Justyna Petke
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  • PersonId : 1129106
Shin Yoo
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  • PersonId : 1286727

Résumé

PyGGI is a research tool for Genetic Improvement (GI), that is designed to be versatile and easy to use. We present version 2.0 of PyGGI, the main feature of which is an XML-based intermediate program representation. It allows users to easily define GI operators and algorithms that can be reused with multiple target languages. Using the new version of PyGGI, we present two case studies. First, we conduct an Automated Program Repair (APR) experiment with the QuixBugs benchmark, one that contains defective programs in both Python and Java. Second, we replicate an existing work on runtime improvement through program specialisation for the MiniSAT satisfiability solver. PyGGI 2.0 was able to generate a patch for a bug not previously fixed by any APR tool. It was also able to achieve 14% runtime improvement in the case of MiniSAT. The presented results show the applicability and the expressiveness of the new version of PyGGI. A video of the tool demo is at: https://youtu.be/PxRUdlRDS40.
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Dates et versions

hal-04215712 , version 1 (22-09-2023)

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Gabin An, Aymeric Blot, Justyna Petke, Shin Yoo. PyGGI 2.0: language independent genetic improvement framework. ESEC/FSE '19: 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Aug 2019, Tallinn, Estonia. pp.1100-1104, ⟨10.1145/3338906.3341184⟩. ⟨hal-04215712⟩
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