An Evaluation of Combination Strategies for Test Case Selection
2006 (English)In: Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 11, no 4, p. 583-611Article in journal (Refereed) Published
Abstract [en]
This paper presents results from a comparative evaluation of five combination strategies. Combination strategies are test case selection methods that combine “interesting” values of the input parameters of a test subject to form test cases. This research comparatively evaluated five combination strategies; the All Combination strategy (AC), the Each Choice strategy (EC), the Base Choice strategy (BC), Orthogonal Arrays (OA) and the algorithm from the Automatic Efficient Test Generator (AETG). AC satisfies n-wise coverage, EC and BC satisfy 1-wise coverage, and OA and AETG satisfy pair-wise coverage. The All Combinations strategy was used as a “gold standard” strategy; it subsumes the others but is usually too expensive for practical use. The others were used in an experiment that used five programs seeded with 128 faults. The combination strategies were evaluated with respect to the number of test cases, the number of faults found, failure size, and number of decisions covered. The strategy that requires the least number of tests, Each Choice, found the smallest number of faults. Although the Base Choice strategy requires fewer test cases than Orthogonal Arrays and AETG, it found as many faults. Analysis also shows some properties of the combination strategies that appear significant. The two most important results are that the Each Choice strategy is unpredictable in terms of which faults will be revealed, possibly indicating that faults are found by chance, and that the Base Choice and the pair-wise combination strategies to some extent target different types of faults.
Place, publisher, year, edition, pages
Springer, 2006. Vol. 11, no 4, p. 583-611
Keywords [en]
Combination strategies, Orthogonal arrays, AETG, Test case selection, Testing experiment
National Category
Engineering and Technology
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-1995DOI: 10.1007/s10664-006-9024-2ISI: 000242805000005OAI: oai:DiVA.org:his-1995DiVA, id: diva2:32271
2008-04-212008-04-212022-09-15Bibliographically approved