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Genetic programming is combined with program analysis methods to repair bugs in off-the-shelf legacy C programs. Fitness is defined using negative test cases that exercise the bug to be repaired and positive test cases that encode program requirements. Once a successful repair is discovered, structural differencing algorithms and delta debugging methods are used to minimize its size. Several modifications to the GP technique contribute to its success: genetic operations are localized to the nodes along the execution path of the negative test case; high-level statements are represented as single nodes in the program tree; genetic operators use existing code in other parts of the program, so new code does not need to be invented.
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