Bandyopadhyay, Aritra, authorGhosh, Sudipto, advisorBieman, James M., committee memberFrance, Robert B., committee memberStrout, Michelle Mills, committee memberTurk, Daniel, committee member2007-01-032007-01-032013http://hdl.handle.net/10217/80137Coincidentally correct test cases are those that execute faulty program statements but do not result in failures. The presence of such test cases in a test suite reduces the effectiveness of spectrum-based fault localization approaches, such as Ochiai and Tarantula, which localize faulty statements by calculating a suspiciousness score for every program statement from test coverage information. The goal of this dissertation is to improve the understanding of how the presence of coincidentally correct test cases impacts the effectiveness of spectrum-based fault localization approaches and to develop a family of approaches that improve fault localization effectiveness by mitigating the effect of coincidentally correct test cases. Each approach (1)~classifies coincidentally correct test cases using test coverage information, and (2)~recalculates a suspiciousness score for every program statement using the classification information. We developed classification approaches using test coverage metrics at different levels of granularity, such as statement, branch, and function. We developed a new approach for ranking program statements using suspiciousness scores calculated based on the heuristic that the statements covered by more failing and coincidentally correct test cases are more suspicious. We extended the family of fault localization approaches to support multiple faults. We developed an approach to incorporate tester feedback to mitigate the effect of coincidental correctness. The approach analyzes tester feedback to determine a lower bound for the number of coincidentally correct test cases present in a test suite. The lower bound is also used to determine when classification of coincidentally correct test cases can improve fault localization effectiveness. We evaluated the fault localization effectiveness of our approaches and studied how the effectiveness changes for varying characteristics of test suites, such as size, test suite type (e.g., random, coverage adequate), and the percentage of passing test cases that are coincidentally correct. Our key findings are summarized as follows. Mitigating the effect of coincidentally correct test cases improved fault localization effectiveness. The extent of the improvement increased with an increase in the percentage of passing test cases that were coincidentally correct, although no improvement was observed when most passing test cases in a test suite were coincidentally correct. When random test suites were used to localize faults, a coarse-grained coverage spectrum, such as function coverage, resulted in better classification than fine-grained coverage spectra, such as statement and branch coverage. Utilizing tester feedback improved the precision of classification. Mitigating the effect of coincidental correctness in the presence of two faults improved the effectiveness for both faults simultaneously for most faulty programs. Faulty statements that were harder to reach and that affected fewer program statements resulted in fewer coincidentally correct test cases and were more effectively localized.born digitaldoctoral dissertationsengCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.software fault localization and debuggingtest selection and classificationstatic and dynamic program analysissoftware testingText