Combinatorial testing has become an important approach in software testing, and many algorithms have been developed for generating combinatorial test cases. However, few have considered the constraints between the input parameters. In this paper, we summarize existing combinatorial testing strategies with constraints and propose two novel algorithms, namely, the CCS (construct constraint set) algorithm and the CTWC (combinatorial testing with constraints) algorithm. We first utilize CCS to compute implied constraints, and then facilitate CTWC to generate test cases for the system under test.We evaluate the CCS algorithm using a case study and compare the results of the CTWC algorithm with some existing strategies.Experimental results show that our algorithm outperformed them in terms of the number of test cases.
Pairwise testing has become an important approach to software testing because it often provides effective error detection at low cost, and a key problem of it is the test case generation method. As the part of an effort to develop an optimized strategy for pairwise testing, this paper proposes an efficient pairwise test case generation strategy, called VIPO(Variant of In-Parameter-order ), which is a variant of IPO strategy. We compare its effectiveness with some existing strategies including IPO, Tconfig, Pict and AllPairs. Experimental results demonstrate that VIPO outperformed them in terms of the number of generated test case within reasonable execution times, in most cases.
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