Automatically Finding Patches Using Genetic Programming

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Automatically Finding Patches Using Genetic Programming (2009)

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by Westley Weimer , ThanhVu Nguyen , Claire Le Goues , Stephanie Forrest

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146 - 24 self

BibTeX

@MISC{Weimer09automaticallyfinding,
    author = {Westley Weimer and ThanhVu Nguyen and Claire Le Goues and Stephanie Forrest},
    title = {Automatically Finding Patches Using Genetic Programming },
    year = {2009}
}

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Abstract

Automatic program repair has been a longstanding goal in software engineering, yet debugging remains a largely manual process. We introduce a fully automated method for locating and repairing bugs in software. The approach works on off-the-shelf legacy applications and does not require formal specifications, program annotations or special coding practices. Once a program fault is discovered, an extended form of genetic programming is used to evolve program variants until one is found that both retains required functionality and also avoids the defect in question. Standard test cases are used to exercise the fault and to encode program requirements. After a successful repair has been discovered, it is minimized using structural differencing algorithms and delta debugging. We describe the proposed method and report experimental results demonstrating that it can successfully repair ten different C programs totaling 63,000 lines in under 200 seconds, on average.

Keyphrases

patch using genetic programming extended form genetic programming off-the-shelf legacy application longstanding goal program variant special coding practice program fault formal specification delta debugging manual process successful repair standard test case program requirement program annotation automatic program repair software engineering report experimental result ten different program

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