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Ensuring that a program operates correctly is a difficult task in large, complex systems.
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The Daikon system for dynamic detection of likely invariants
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On the naturalness of software. In 2012 34th International Conference on Software Engineering (ICSE) . IEEE, 837–847
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Gated graph sequence neural networks
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Toward Deep Learning Software Repositories. In Proceedings of the 12th Working Conference on Mining Software Repositories (MSR ’15) . IEEE Press, Piscataway, NJ, USA, 334–345
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Are deep neural networks the best choice for modeling source code?. In Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering . ACM, 763–773
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Assertion generation through active learning. In International Conference on Formal Engineering Methods . Springer, 174–191
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Mining Semantic Loop Idioms
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Learning to Represent Programs with Graphs. In International Conference on Learning Representations
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Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, et al · 2016
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Learning invariants using decision trees and implication counterexamples. In Acm Sigplan Notices , Vol. 51. ACM, 499–512
Pranav Garg, Daniel Neider, Parthasarathy Madhusudan, and Dan Roth. 2016 · 2016
Cited alongside, same era.
Data-driven precondition inference with learned features
Saswat Padhi, Rahul Sharma, and Todd Millstein. 2016 · 2016
Cited alongside, same era.
On the “naturalness” of buggy code. In 2016 IEEE/ACM 38th International Conference on Software Engineering (ICSE) . IEEE, 428–439
Baishakhi Ray, Vincent Hellendoorn, Saheel Godhane, Zhaopeng Tu, Alberto Bacchelli, and Premkumar Devanbu. 2016 · 2016
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Learning shape analysis. In International Static Analysis Symposium . Springer, 66–87
Marc Brockschmidt, Yuxin Chen, Pushmeet Kohli, Siddharth Krishna, and Daniel Tarlow. 2017 · 2017
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Source code for DotLiquid.Template.RegisterSafeType(Type type, string[] allowedMembers)
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Cited in the paper.
Source code for Log4Net.Appender.FileAppender.WriteHeader()
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Cited in the paper.
Source code for MetricsṄet: MetricsĊoreĊounterMetricİncrement()
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Cited in the paper.
Vincent J. Hellendoorn, Christian Bird, Earl T. Barr, and Miltiadis Allamanis. 2018 · 2018
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DeepBugs: A Learning Approach to Name-based Bug Detection
Michael Pradel and Koushik Sen. 2018 · 2018
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Learning loop invariants for program verification. In Advances in Neural Information Processing Systems . 7762–7773
Xujie Si, Hanjun Dai, Mukund Raghothaman, Mayur Naik, and Le Song. 2018 · 2018
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Dynamic Neural Program Embeddings for Program Repair. In International Conference on Learning Representations
Ke Wang, Zhendong Su, and Rishabh Singh. 2018 · 2018
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Generative Code Modeling with Graphs. In International Conference on Learning Representations
Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt, and Oleksandr Polozov. 2019 · 2019
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