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In Software Engineering (ICSE), 2012 34th International Conference on (June 2012), pp. 3-13, doi:10.1109/icse.2012.6227211 Key: citeulike:11919206
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There are more bugs in real-world programs than human programmers can realistically address. This paper evaluates two research questions: “What fraction of bugs can be repaired automatically?” and “How much does it cost to repair a bug automatically?” In previous work, we presented GenProg, which uses genetic programming to repair defects in off-the-shelf C programs. To answer these questions, we: (1) propose novel algorithmic improvements to GenProg that allow it to scale to large programs and find repairs 68% more often, (2) exploit GenProg's inherent parallelism using cloud computing resources to provide grounded, human-competitive cost measurements, and (3) generate a large, indicative benchmark set to use for systematic evaluations. We evaluate GenProg on 105 defects from 8 open-source programs totaling 5.1 million lines of code and involving 10,193 test cases. GenProg automatically repairs 55 of those 105 defects. To our knowledge, this evaluation is the largest available of its kind, and is often two orders of magnitude larger than previous work in terms of code or test suite size or defect count. Public cloud computing prices allow our 105 runs to be reproduced for $403; a successful repair completes in 96 minutes and costs $7.32, on average.
GenProg update to represent changes as diffs (patches) rather than weighted path + AST to allow scaling to larger programs. Tested on repo history of programs (so looking for bugs already found and repaired manually in future revisions as success). Run on cloud platform for cost metric and scaling to long parallel execution.
State of the art Genetic Programming, Evolutionary repair generation.
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