Regression test suite minimization using integer linear programming model

S Panda, DP Mohapatra - Software: Practice and Experience, 2017 - Wiley Online Library
Software: Practice and Experience, 2017Wiley Online Library
Software testers always face the dilemma of whether to retest the software with all the test
cases or select a few of them on the basis of their fault detection ability. This paper
introduces a novel approach to minimizing the test suite as an integer linear programming
problem with optimal results. The minimization method uses the cohesion values of the
program parts affected by the changes made to the program. The hypothesis is that the
program parts with low cohesion values are more prone to errors. This assumption is …
Summary
Software testers always face the dilemma of whether to retest the software with all the test cases or select a few of them on the basis of their fault detection ability. This paper introduces a novel approach to minimizing the test suite as an integer linear programming problem with optimal results. The minimization method uses the cohesion values of the program parts affected by the changes made to the program. The hypothesis is that the program parts with low cohesion values are more prone to errors. This assumption is validated on the mutation fault detection ability of the test cases. The experimental study carried out on 30 programs evaluates the effectiveness and usefulness of the proposed framework. The experimental results show that the minimized test suite can efficiently reveal the errors and ensure acceptable software quality. Copyright © 2017 John Wiley & Sons, Ltd.
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