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ISSTA 2018
Sun 15 - Sat 21 July 2018 Amsterdam, Netherlands
co-located with ECOOP and ISSTA 2018
Mon 16 Jul 2018 16:20 - 16:40 at Zurich II - Machine Learning Chair(s): Alex Orso

Formal specifications are essential but usually unavailable in software systems. Furthermore, writing these specifications is costly and requires skills from developers. Recently, many automated techniques have been proposed to mine specifications in various formats including finite-state automaton (FSA). However, more works in specification mining are needed to further improve the accuracy of the inferred specifications.

In this work, we propose Deep Specification Miner (DSM), a new approach that performs deep learning for mining FSA-based specifications. Our proposed approach uses test case generation to generate a rich set of execution traces for training a Recurrent Neural Network Based Language Model (RNNLM). From these execution traces, we construct a Prefx Tree Acceptor (PTA) and use the learned RNNLM to extract many features. These features are subsequently utilized by clustering algorithms to merge similar automata states in PTA for constructing a number of FSAs. Then, our approach performs a model selection heuristic to estimate F-measure of FSAs and returns the one with highest estimated F-measure. We execute DSM to mine specifications of 11 target library classes. Our empirical analysis shows that DSM achieves an average Precision, Recall, and F-measure of 82.76%, 72.3%, and 71.97%, respectively. Compared to the best baseline, our approach is more effective by 28.22% in terms of average F-measure

Mon 16 Jul
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16:00 - 17:30: Machine LearningISSTA Technical Papers at Zurich II
Chair(s): Alex OrsoGeorgia Institute of Technology
16:00 - 16:20
Compiler Fuzzing through Deep LearningDistinguished Paper
ISSTA Technical Papers
Chris CumminsUniversity of Edinburgh, Pavlos PetoumenosUniversity of Edinburgh, Alastair MurrayCodeplay Software, Hugh LeatherUniversity of Edinburgh
16:20 - 16:40
Deep Specification Mining
ISSTA Technical Papers
Tien-Duy B. LeSchool of Information Systems, Singapore Management University, David LoSingapore Management University
16:40 - 17:00
Identifying Implementation Bugs in Machine Learning based Image Classifiers using Metamorphic Testing
ISSTA Technical Papers
Anurag DwarakanathAccenture Labs, Manish AhujaAccenture Labs, Samarth SikandAccenture Labs, Raghotham M RaoAccenture Labs, R.P. Jagadeesh Chandra BoseAccenture Labs, Neville DubashAccenture Labs, Sanjay Podder
17:00 - 17:20
An Empirical Study on TensorFlow Program Bugs
ISSTA Technical Papers
Yuhao ZhangPeking University, Yifan ChenPeking University, Shing-Chi CheungDepartment of Computer Science and Engineering, The Hong Kong University of Science and Technology, Yingfei XiongPeking University, Lu ZhangPeking University
17:20 - 17:30
Q&A in groups
ISSTA Technical Papers