Generating cost-aware covering arrays for free

Software systems generally have a large number of configurable options interacting with each other. Such systems are more likely to be prone to errors, crashes, and faulty executions that are usually caused by option interactions. To avoid such errors, testing all possible configurations during the development phase is usually not feasible, since the number of all possible configurations is exponential in the order of number of options. A t-way covering array (CA) is a 2-dimensional combinatorial object that helps to efficiently cover all t-length option interactions of the system under test. Generating a CA with a small number of configurations is important to shorten the testing phase. However, the testing cost (e.g. the testing time) may differ from one configuration to another. Currently, most sequential tools can generate optimum CAs in terms of number of configurations, but they are not cost-aware, i.e., they cannot handle the varying costs of configurations. In this work, we implement a parallel, cost-aware CA-generation tool based on a sequential tool, Jenny, to generate lower-cost CAs faster. Experimental results show that our cost-aware CA construction approach can generate 32% and 21% lower cost CAs on average for t = 2 and t = 3, respectively, compared to state-of-the-art CA-generation tools. Moreover, the cost-awareness comes for free, i.e., we speed up our algorithm by leveraging parallel computation. The cost models and cost reduction techniques we propose could also be adapted for other existing CA generation tools

Generating cost-aware covering arrays for free

Software systems generally have a large number of configurable options interacting with each other. Such systems are more likely to be prone to errors, crashes, and faulty executions that are usually caused by option interactions. To avoid such errors, testing all possible configurations during the development phase is usually not feasible, since the number of all possible configurations is exponential in the order of number of options. A t-way covering array (CA) is a 2-dimensional combinatorial object that helps to efficiently cover all t-length option interactions of the system under test. Generating a CA with a small number of configurations is important to shorten the testing phase. However, the testing cost (e.g. the testing time) may differ from one configuration to another. Currently, most sequential tools can generate optimum CAs in terms of number of configurations, but they are not cost-aware, i.e., they cannot handle the varying costs of configurations. In this work, we implement a parallel, cost-aware CA-generation tool based on a sequential tool, Jenny, to generate lower-cost CAs faster. Experimental results show that our cost-aware CA construction approach can generate 32% and 21% lower cost CAs on average for t = 2 and t = 3, respectively, compared to state-of-the-art CA-generation tools. Moreover, the cost-awareness comes for free, i.e., we speed up our algorithm by leveraging parallel computation. The cost models and cost reduction techniques we propose could also be adapted for other existing CA generation tools