Research On Combinatorial Testing For Generating Feature Configurations Of Software Product Line

Early validation of core assets as well as their combinations in domain engineering is an essential assurance for the success of software product line (SPL) engineering. By feature-driven approaches, variability configurations can be constructed and tested from the business perspective, thus supports to uncover defects caused by the unintended feature interactions. Combinatorial testing (CIT) is adopted as a sampling technique to avoid the combination explosion problem. Based on the traceability links from features to components, a feature configuration can be mapped to a set of selected components and their integrations. However, the generated feature configurations should be further prioritized to help allocate restricted time and budget in domain testing.In the paper, we propose a framework to generate and prioritize feature configurations for SPL integration testing. The framework follows the idea of CIT and is based on the pair-wise feature interaction coverage. In addition, the feature configurations are sorted as they are built according to their importance to SPL testing.The framework applied on weighted feature models involves the activities including feature model flattening, configuration model transformation, constraint deduction and P-CIT algorithm execution. We’ve proposed two CIT algorithms, P-AETG and PICT fitting our framework by now. The framework is applied and validated by an Online Exam Product Line. In addition, it is further applied to weighted feature models from SPLOT to evaluate its performance and effectiveness.