With new algorithms and tools, developers can apply high-strength combinatorial testing to detect elusive failures that occur only when multiple components interact. In pairwise testing, all possible pairs of parameter values are covered by at least one test, and good tools are available to generate... See full abstract

With new algorithms and tools, developers can apply high-strength combinatorial testing to detect elusive failures that occur only when multiple components interact. In pairwise testing, all possible pairs of parameter values are covered by at least one test, and good tools are available to generate arrays with the value pairs. In the past few years, advances in covering-array algorithms, integrated with model checking or other testing approaches, have made it practical to extend combinatorial testing beyond pairwise tests. The US National Institute of Standards and Technology (NIST) and the University of Texas, Arlington, are now distributing freely available methods and tools for constructing large t-way combination test sets (known as covering arrays), converting covering arrays into executable tests, and automatically generating test oracles using model checking (http://csrc.nist.rip/acts). In this review, we focus on real-world problems and empirical results from applying these methods and tools.
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