Mutation testing can be used to assess the fault-detection capabilities of a given test suite. To this aim, two characteristics of mutation testing frameworks are of paramount importance: (i) they should generate mutants that are representative of real faults; and (ii) they should provide a complete tool chain able to automatically generate, inject, and test the mutants. To address the first point, we recently proposed an approach using a Recurrent Neural Network EncoderDecoder architecture to learn mutants from ∼787k faults mined from real programs. The empirical evaluation of this approach confirmed its ability to generate mutants representative of real faults. In this paper, we address the second point, presenting DeepMutation, a tool wrapping our deep learning model into a fully automated tool chain able to generate, inject, and test mutants learned from real faults. Video: https://sites.google.com/view/learningmutation/deepmutation
Fri 10 JulDisplayed time zone: (UTC) Coordinated Universal Time change
16:05 - 17:05 | A24-Testing and Debugging 4Technical Papers / New Ideas and Emerging Results / Journal First / Demonstrations at Silla Chair(s): Yijun Yu The Open University, UK | ||
16:05 6mTalk | Manifold for Machine Learning AssuranceNIER New Ideas and Emerging Results | ||
16:11 12mTalk | On Learning Meaningful Assert Statements for Unit Test CasesTechnical Technical Papers Cody Watson Washington and Lee University, Michele Tufano Microsoft, Kevin Moran William & Mary/George Mason University, Gabriele Bavota Università della Svizzera italiana, Denys Poshyvanyk William and Mary Pre-print Media Attached | ||
16:23 12mTalk | TRADER: Trace Divergence Analysis and Embedding Regulation for Debugging Recurrent Neural Networks Technical Papers Guanhong Tao Purdue University, Shiqing Ma Rutgers University, Yingqi Liu Purdue University, USA, Qiuling Xu Purdue University, Xiangyu Zhang Purdue University Pre-print | ||
16:35 3mTalk | DeepMutation: A Neural Mutation ToolDemo Demonstrations Michele Tufano Microsoft, Jason Kimko William & Mary, Shiya Wang William & Mary, Cody Watson Washington and Lee University, Gabriele Bavota Università della Svizzera italiana, Massimiliano Di Penta University of Sannio, Denys Poshyvanyk William and Mary Pre-print | ||
16:38 8mTalk | Specification Patterns for Robotic MissionsJ1 Journal First Claudio Menghi University of Luxembourg, Christos Tsigkanos TU Vienna, Patrizio Pelliccione University of L'Aquila and Chalmers | University of Gothenburg, Carlo Ghezzi Politecnico di Milano, Thorsten Berger Chalmers | University of Gothenburg | ||
16:46 8mTalk | ProXray: Protocol Model Learning and Guided Firmware AnalysisJ1 Journal First Farhaan Fowze University of Florida, Dave (Jing) Tian Purdue University, Grant Hernandez University of Florida, Kevin Butler Univ. Florida, Tuba Yavuz University of Florida | ||
16:54 6mTalk | Visual Sketching: From Image Sketches to CodeNIER New Ideas and Emerging Results Marcelo d'Amorim Federal University of Pernambuco, Rui Abreu Instituto Superior Técnico, U. Lisboa & INESC-ID, Carlos Mello Federal University of Pernambuco Pre-print Media Attached | ||