• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1089-1102
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• 2017

In software systems, it has been observed that a fault is often caused by an interaction between a small number of input parameters. Even for moderately sized software systems, exhaustive testing is practically impossible to achieve. This is either due to time or cost constraints. Combinatorial (t-way) testing provides a technique to select a subset of exhaustive test cases covering all of the t-way interactions, without much of a loss to the fault detection capability. In this paper, an approach is proposed to generate 2-way (pairwise) test sets using genetic algorithms. The performance of the algorithm is improved by creating an initial solution using the overlap coefficient (a similarity matrix). Two mutation strategies have also been modified to improve their efficiency. Furthermore, the mutation operator is improved by using a combination of three mutation strategies. A comparative survey of the techniques to generate t-way test sets using genetic algorithms was also conducted. It has been shown experimentally that the proposed approach generates faster results by achieving higher percentage coverage in a fewer number of generations. Additionally, the size of the mixed covering arrays was reduced in one of the six benchmark problems examined.

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.565-579
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• 1997

A robust test is proposed for the problem of testing the parallelism of several regression lines against ordered alternatives. The proposed test statistic is based on a linear combination of one-step pairwise GM-estimators. We compare the performance of the proposed test with that of the other tests through a Monte Carlo simulation. The results of the simulation study show that the proposed test has stable levels, good empirical powers in various circumstances, and particularly higher empirical powers under the presence of extreme outliers or leverage points.

• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.469-480
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• 2014

Software Product Line (SPL) is a software development paradigm that guarantees high productivity, reduced cost, and shorter time-to-market by systematically planning and reusing commonality and variability. In order to maximize the benefits of SPL engineering, testing should be integrated into the SPL engineering lifecycle processes that consist of domain engineering and application engineering and should be performed with as little test efforts as possible. This paper proposes a systematic software product line test cases derivation method using combinatorial test design. By applying combinatorial test design to product line test cases derivation and exploiting commonality between products at the same time, the number of generated test cases is dramatically reduced with the result that they can be effectively reused by the products of the given product line. Case studies conducted in this paper show the efficacy of our method compared with other methods that use only commonality or combinatorial design or neither of them in terms of the number of derived test cases.