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Regression test suite minimization using integer linear programming model
Author(s) -
Panda S.,
Mohapatra D. P.
Publication year - 2017
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2485
Subject(s) - regression testing , cohesion (chemistry) , test suite , computer science , integer programming , suite , linear programming , software , minification , software quality , fault detection and isolation , test case , reliability engineering , regression analysis , algorithm , machine learning , artificial intelligence , programming language , engineering , software development , software construction , chemistry , organic chemistry , archaeology , actuator , history
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.