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- W2014886770 abstract "Software testing is an effective, yet expensive, method to improve software quality. Test automation, a potential way to reduce testing cost, has received enormous research attention recently, but the so-called “oracle problem” (how to decide the PASS/FAIL outcome of a test execution) is still a major obstacle to such cost reduction. We have extensively investigated state-of-the-art works that contribute to address this problem, from areas such as specification mining and model inference. In this paper, we compare three types of automated oracles: Data invariants, Temporal invariants, and Finite State Automata. More specifically, we study the training cost and the false positive rate; we evaluate also their fault detection capability. Seven medium to large, industrial application subjects and real faults have been used in our empirical investigation." @default.
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- W2014886770 date "2013-08-18" @default.
- W2014886770 modified "2023-09-23" @default.
- W2014886770 title "Automated oracles: an empirical study on cost and effectiveness" @default.
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- W2014886770 doi "https://doi.org/10.1145/2491411.2491434" @default.
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