Generally, systematic testing is the only way to assess the occurrence of failures in systems consisting in a set of components, however given the size of real-world systems, it would be very expensive to construct and test all the possible combinations of the states of components. Combinatorial interaction testing is an existing tecnique that appropriately reduces the number of test cases by choosing either pairs, triplets, etc., i.e. t-tuples, of input values. Of course, the effectiveness of a test suite is higher when choosing e.g. triplets of inputs rather than pairs. Since high values of t are preferable, a large number of test cases could still be generated. This paper proposes a technique for building the smallest possible test suite of size t. This technique consists in reducing the number of test cases by carefully choosing non redundant t-tuples. The paper shows that for obtaining the smallest possible set of tests, it is best to generate a large 'flexible' set of t-tuples and then reduce such a set until the smallest one is obtained. Reduction is a computationally expensive operation and therefore it is worth performing it by parallelising its execution. This paper proposes a solution for executing the reduction algorithm over a set of Grid resources.
(2009). Building T-wise Combinatorial Interaction Test Suites by Means of Grid Computing [conference presentation - intervento a convegno]. Retrieved from http://hdl.handle.net/10446/23391
Building T-wise Combinatorial Interaction Test Suites by Means of Grid Computing
GARGANTINI, Angelo Michele;
2009-01-01
Abstract
Generally, systematic testing is the only way to assess the occurrence of failures in systems consisting in a set of components, however given the size of real-world systems, it would be very expensive to construct and test all the possible combinations of the states of components. Combinatorial interaction testing is an existing tecnique that appropriately reduces the number of test cases by choosing either pairs, triplets, etc., i.e. t-tuples, of input values. Of course, the effectiveness of a test suite is higher when choosing e.g. triplets of inputs rather than pairs. Since high values of t are preferable, a large number of test cases could still be generated. This paper proposes a technique for building the smallest possible test suite of size t. This technique consists in reducing the number of test cases by carefully choosing non redundant t-tuples. The paper shows that for obtaining the smallest possible set of tests, it is best to generate a large 'flexible' set of t-tuples and then reduce such a set until the smallest one is obtained. Reduction is a computationally expensive operation and therefore it is worth performing it by parallelising its execution. This paper proposes a solution for executing the reduction algorithm over a set of Grid resources.Pubblicazioni consigliate
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