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In Proceedings of the 2008 GECCO conference companion on Genetic and evolutionary computation (2008), pp. 1819-1822, doi:10.1145/1388969.1388979 Key: citeulike:11370636
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In evolutionary testing, meta-heuristic search techniques are used to generate high-quality test data. The focus of our on-going work is on employing evolutionary algorithms for the structural unit-testing of object-oriented Java programs. Test cases are evolved using the Strongly-Typed Genetic Programming technique. Test data quality evaluation includes instrumenting the test object, executing it with the generated test cases, and tracing the structures traversed in order to derive coverage metrics. The strategy for efficiently guiding the search process towards achieving full structural coverage involves favouring test cases that exercise problematic structures and control-flow paths. Static analysis and instrumentation is performed solely with basis on the information extracted from the test objects' Java Bytecode. Relevant contributions include the introduction of novel methodologies for automation, search guidance and input domain reduction, and the presentation of the eCrash automated test case generation tool.
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