Measuring Effectiveness of Sample-based Product-Line Testing
Recent research on quality assurance (QA) of configurable software systems (e.g., software product lines) proposes different analysis strategies to cope with the inherent complexity caused by the well-known combinatorial-explosion problem. Those strategies aim at improving efficiency of QA techniques like software testing as compared to brute-force configuration-by-configuration analysis. Sampling constitutes one of the most established strategies, defining criteria for selecting a drastically reduced, yet sufficiently diverse subset of software configurations considered during QA. However, finding generally accepted measures for assessing the impact of sample-based analysis on the effectiveness of QA techniques is still an open issue. We address this problem by lifting concepts from single-software mutation testing to configurable software. Our framework incorporates a rich collection of mutation operators for product lines implemented in C to measure mutation scores of samples, including a novel family-based technique for product-line mutation detection. Our experimental results gained from applying our tool implementation to a collection of subject systems confirms the widely-accepted assumption that pairwise sampling constitutes the most reasonable efficiency/effectiveness trade-off for sample-based product-line testing.
Tue 6 NovDisplayed time zone: Guadalajara, Mexico City, Monterrey change
10:30 - 12:00 | |||
10:30 30mTalk | Measuring Effectiveness of Sample-based Product-Line Testing GPCE 2018 Sebastian Ruland , Lars Luthmann TU Darmstadt, Real-time Systems Lab, Johannes Bürdek TU Darmstadt, Real-time Systems Lab, Sascha Lity Technische Universität Braunschweig, Thomas Thüm University of Ulm, Malte Lochau , Márcio Ribeiro Federal University of Alagoas, Brazil | ||
11:00 30mTalk | Pattern Matching in an Open World GPCE 2018 | ||
11:30 30mTalk | Verification of High-Level Transformations with Inductive Refinement Types GPCE 2018 Ahmad Salim Al-Sibahi Department of Computer Science, University of Copenhagen (DIKU) & BilagScan, Thomas P. Jensen INRIA Rennes, Aleksandar S. Dimovski IT University of Copenhagen, Denmark, Andrzej Wąsowski IT University of Copenhagen, Denmark |