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Model-Based Software Regression Test Suite Reduction
Abstract:In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1107347Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1391
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 Y. Chen, Specification-based Regression Test Suite Generation and Reduction, Ph.D. thesis, University of Ottawa, Canada, 2009.