Evaluating evolutionary testability with software-measurements

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Abstract

Test case design is the most important test activity with respect to test quality. For this reason, a large number of testing methods have been developed to assist the tester with the definition of appropriate, error-sensitive test data. Besides black-box tests, white-box tests are the most prevalent. In both cases, complete automation of test case design is difficult. Automation of black-box test is only meaningfully possible if a formal specification exists, and, due to the limits of symbolic execution, tools supporting white-box tests are limited to program code instrumentation and coverage measurement. Evolutionary testing is a promising approach for automating structure-oriented test case design completely. In many experiments, high coverage degrees were reached using evolutionary testing. In this paper we shall investigate the suitability of structure-based complexity measures to assess whether or not evolutionary testing is appropriate for the structure-oriented test of given test objects. © Springer-Verlag Berlin Heidelberg 2004.

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Lammermann, F., Baresel, A., & Wegener, J. (2004). Evaluating evolutionary testability with software-measurements. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3103, 1350–1362. https://doi.org/10.1007/978-3-540-24855-2_156

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