Multi-objective regression test-selection in practice: an industrial case study

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2017

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Özkan, Ramazan

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Regression testing is testing of previously verified parts of a software system to make sure that software changes do not affect those parts. However running an entire regression test suite after every code change may be costly or even infeasible due to time and resource constraints especially in large-scale software projects. In order to resolve this issue and optimize the number of test cases to be rerun for regression, several techniques have been proposed in the literature. One of these is Multi-Objective Regression Test Optimization (MORTO) approach. This thesis is an “action research”-based empirical study to improve regression test-selection process of an industrial project, in the defence sector, based on the MORTO approach, in which the problem is formulated and solved by using a genetic algorithm. The empirical results demonstrate that this approach yields a more efficient test suite based on a set of five cost objectives, four value objectives and a dependency while providing full requirements coverage.

Subject Keywords

Genetic algorithms., Regression analysis., Mathematical optimization., Computer software

URI

http://etd.lib.metu.edu.tr/upload/12620692/index.pdf
https://hdl.handle.net/11511/26225

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Graduate School of Informatics, Thesis

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Citation Formats

R. Özkan, “Multi-objective regression test-selection in practice: an industrial case study,” M.S. - Master of Science, Middle East Technical University, 2017.