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.
Fri 13 NovDisplayed time zone: (UTC) Coordinated Universal Time change
08:00 - 08:30 | |||
08:00 2mTalk | Baital: An Adaptive Weighted Sampling Approach for Improved t-wise Coverage Research Papers Eduard Baranov Université Catholique de Louvain, Belgium, Axel Legay Université Catholique de Louvain, Belgium, Kuldeep S. Meel National University of Singapore, Singapore DOI | ||
08:03 1mResearch paper | Cost Measures Matter for Mutation Testing Study Validity Research Papers Giovani Guizzo University College London, UK, Federica Sarro University College London, UK, Mark Harman University College London, UK DOI Pre-print | ||
08:05 1mTalk | Developing and Evaluating Objective Termination Criteria for Random Testing Journal First Porfirio Tramontana Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Italy, Domenico Amalfitano University of Naples Federico II, Nicola Amatucci Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Italy, Atif Memon Apple Inc., Anna Rita Fasolino Federico II University of Naples | ||
08:07 1mTalk | Efficient Binary-Level Coverage Analysis Research Papers M. Ammar Ben Khadra TU Kaiserslautern, Germany, Dominik Stoffel TU Kaiserslautern, Germany, Wolfgang Kunz TU Kaiserslautern, Germany DOI Pre-print Media Attached | ||
08:09 1mTalk | Efficiently Finding Higher-Order Mutants Research Papers Chu-Pan Wong Carnegie Mellon University, USA, Jens Meinicke Carnegie Mellon University, USA, Leo Chen Carnegie Mellon University, USA, João Paulo Diniz Federal University of Minas Gerais, Brazil, Christian Kästner Carnegie Mellon University, USA, Eduardo Figueiredo Federal University of Minas Gerais, Brazil DOI | ||
08:11 1mTalk | Selecting Fault Revealing Mutants Journal First Thierry Titcheu Chekam University of Luxembourg (SnT), Mike Papadakis University of Luxembourg, Luxembourg, Tegawendé F. Bissyandé University of Luxembourg, Luxembourg, Yves Le Traon University of Luxembourg, Luxembourg, Koushik Sen University of California at Berkeley | ||
08:13 17mTalk | Conversations on Testing 3 Paper Presentations Chu-Pan Wong Carnegie Mellon University, USA, Eduard Baranov Université Catholique de Louvain, Belgium, Giovani Guizzo University College London, UK, M. Ammar Ben Khadra TU Kaiserslautern, Germany, Porfirio Tramontana Department of Electrical Engineering and Information Technologies, University of Naples Federico II, Italy, Thierry Titcheu Chekam University of Luxembourg (SnT), M: Marcel Böhme Monash University, Australia | ||