Recast IPOG-D Algorithm with Constraint Handling for Combinatorial Testing

Testing is considered as indispensable part in the development process life cycle of any software. Testing is performed to improve the performance, quality and reliability of the software. Designing of relevant test cases plays a major role in deciding the quality of testing. Hence test case designing activity is crucial for the success of testing. Combinatorial strategies are one of those most extensively used methods for generating test cases. These strategies detect failures which are caused by interactions of parameters in the Software under Test(SUT) and by using some sampling mechanisms a covering array test suite is generated. With increase in the number of parameter coverage, the t-way test size sets also increase exponentially which would result in explosion problem. This paper presents a technique to generate minimal test suites in Combinatorial testing(CT). Optimization technique used is Greedy computation strategy for mutation and selection of test cases, used in selecting the locally worst test case for elimination. That is the test case that does not cover maximum number of uncovered interactions from a pool of candidate test cases. Additionally, Branch and bound technique is used for cross over. It is used to branch for the possibilities of number of test cases as cross over inputs. If a particular test case is not possible the bounding happens, else branched for further selection of test cases as input. Experimental results show that Recast Ipog-D generates better/comparable results as compared to the existing algorithm. Additionally, Recast IPOG-D has also contributed to enhance many known Variable Strength Covering array(VSCA) that exist in literature.