Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage
The rise of highly configurable complex software and its widespread usage requires design of efficient testing methodology. t-wise coverage is a leading metric to measure the quality of the testing suite and the underlying test generation engine. While uniform sampling-based test generation is widely believed to be the state of the art approach to achieve t-wise coverage in presence of constraints on the set of configurations, such a scheme often fails to achieve high t-wise coverage in presence of complex constraints. In this work, we propose a novel approach Baital, based on adaptive weighted sampling using literal weighted functions, to generate test sets with high t-wise coverage. We demonstrate that our approach reaches significantly higher t-wise coverage than uniform sampling. The novel usage of literal weighted sampling leaves open several interesting directions, empirical as well as theoretical, for future research.
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| 08:00 - 08:02 Talk | Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage Research Papers Eduard BaranovUniversité Catholique de Louvain, Belgium, Axel LegayUniversité Catholique de Louvain, Belgium, Kuldeep S. MeelNational University of Singapore, Singapore DOI | ||
| 08:03 - 08:04 Research paper | Cost Measures Matter for Mutation Testing Study Validity Research Papers Giovani GuizzoUniversity College London, UK, Federica SarroUniversity College London, UK, Mark HarmanUniversity College London, UK DOI Pre-print | ||
| 08:05 - 08:06 Talk | Developing and Evaluating Objective Termination Criteria for Random Testing Journal First Porfirio TramontanaDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Italy, Domenico AmalfitanoUniversity of Naples Federico II, Nicola AmatucciDepartment of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Italy, Atif MemonApple Inc., Anna Rita FasolinoFederico II University of Naples | ||
| 08:07 - 08:08 Talk | Efficient Binary-Level Coverage Analysis Research Papers M. Ammar Ben KhadraTU Kaiserslautern, Germany, Dominik StoffelTU Kaiserslautern, Germany, Wolfgang KunzTU Kaiserslautern, Germany DOI Pre-print Media Attached | ||
| 08:09 - 08:10 Talk | Efficiently Finding Higher-Order Mutants Research Papers Chu-Pan WongCarnegie Mellon University, USA, Jens MeinickeCarnegie Mellon University, USA, Leo ChenCarnegie Mellon University, USA, João P. DinizFederal University of Minas Gerais, Brazil, Christian KästnerCarnegie Mellon University, USA, Eduardo FigueiredoFederal University of Minas Gerais, Brazil DOI | ||
| 08:11 - 08:12 Talk | Selecting Fault Revealing Mutants Journal First Thierry Titcheu ChekamUniversity of Luxembourg (SnT), Mike PapadakisUniversity of Luxembourg, Luxembourg, Tegawendé F. BissyandéUniversity of Luxembourg, Luxembourg, Yves Le TraonUniversity of Luxembourg, Luxembourg, Koushik SenUniversity of California at Berkeley | ||
| 08:13 - 08:30 Talk | Conversations on Testing 3 Paper Presentations Chu-Pan WongCarnegie Mellon University, USA, Eduard BaranovUniversité Catholique de Louvain, Belgium, Giovani GuizzoUniversity College London, UK, M. Ammar Ben KhadraTU Kaiserslautern, Germany, Porfirio TramontanaDepartment of Electrical Engineering and Information Technologies, University of Naples Federico II, Italy, Thierry Titcheu ChekamUniversity of Luxembourg (SnT), M: Marcel BöhmeMonash University, Australia | ||