earticle

영어

Pairwise testing is known to be effective in finding errors while considering only a small fraction of input space. Recently, a new testing technique that generates pairwise tests from the cause-effect graph has been presented. This technique assumes the use of the Alloy analyzer to generate pairwise tests from the cause-effect graph. Since, however, the Alloy analyzer does not support APIs that build and manipulate the Alloy formulas, the task of test generation may be tedious and error-prone. In this paper, we introduce a tool named CEGPairGen that automates the process of generating pairwise tests from the cause-effect graph without any human intervention. CEGPairGen produces a test generator written in Java KodKod APIs that generates pairwise tests from a given cause-effect graph. KodKod has been designed to efficiently construct, manipulate, and solve constraints. CEGPairGen takes an incremental test generation strategy for situations where the number of pairs to be covered grows quickly. We show a case study where experimental assessment of tests produced by CEGPairGen has been carried out.