Higher-order mutation has the potential for improving major drawbacks of
traditional first-order mutation, such as by simulating more realistic faults
or improving test-optimization techniques. Despite interest in studying
promising higher-order mutants, such mutants are difficult to find due to the
exponential search space of mutation combinations. State-of-the-art
approaches rely on genetic search, which is often incomplete and expensive
due to its stochastic nature. First, we propose a novel way of finding a
complete set of higher-order mutants by using variational execution, a
technique that can, in many cases, explore large search spaces completely and
often efficiently. Second, we use the identified complete set of higher-order
mutants to study their characteristics. Finally, we use the identified
characteristics to design and evaluate a new search strategy, independent of
variational execution, that is highly effective at finding higher-order
mutants even in large codebases.
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 | ||