Test-Suite Prioritisation by Application Navigation Tree Mining

Software tend to evolve over time and so does the test-suite. Regression testing is aimed at assessing that the software evolution did not compromise the working of the existing software components. However, as the software and consequently the test-suite grow in size, the execution of the entire test-suite for each new build becomes infeasible. Techniques like test-suite selection, test-suite minimisation and test-suite prioritisation have been proposed in literature for regression testing. Whilst all of these techniques are essentially an attempt to reduce the testing effort, test-suite selection and minimisation reduce the test-suite size whereas test-suite prioritisation provides a priority order of the test cases without changing the test-suite size. In this work, we focus on test-suite prioritisation. Recently, techniques from data mining have been used for test-suite prioritisation which consider the frequent pairs of interaction among the application interaction patterns. We propose test-Suite prioritisation by Application Navigation Tree mining (t-SANT). First, we construct an application navigation tree by way of extracting both tester and user interaction patterns. Next, we extract frequent sequences of interaction using a sequence mining algorithm inspired from sequential pattern mining. The most frequent longest sequences are assumed to model complex and most frequently used work-flows and hence a prioritisation algorithm is proposed that prioritises the test cases based on the most frequent and longest sequences. We show the usefulness of the proposed scheme with the help of two case studies, an online book store and calculator.