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Recent advances in neural modeling for bug detection have been very promising.
Finding bugs is easy
David Hovemeyer and William Pugh · 2004
Earlier work this paper cites.
The art of software security assessment: Identifying and preventing software vulnerabilities
Mark Dowd, John McDonald, and Justin Schuh · 2006
Earlier work this paper cites.
The google findbugs fixit
Nathaniel Ayewah and William Pugh · 2010
Earlier work this paper cites.
Why don’t software developers use static analysis tools to find bugs?
Brittany Johnson, Yoonki Song, Emerson Murphy-Hill, and Robert Bowdidge · 2013
Earlier work this paper cites.
Portfolio: Searching for relevant functions and their usages in millions of lines of code
Collin Mcmillan, Denys Poshyvanyk, Mark Grechanik, Qing Xie, and Chen Fu · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
Cited alongside, same era.
On the capability of static code analysis to detect security vulnerabilities
Katerina Goseva-Popstojanova and Andrei Perhinschi · 2015
Cited alongside, same era.
Learning to represent programs with graphs
Miltiadis Allamanis, Marc Brockschmidt, and Mahmoud Khademi · 2017
Cited alongside, same era.
Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
Cited alongside, same era.
Deep code comment generation
Xing Hu, Ge Li, Xin Xia, David Lo, and Zhi Jin · 2018
Cited alongside, same era.
Deepbugs: A learning approach to name-based bug detection
Michael Pradel and Koushik Sen · 2018
Later among the works it cites.
code2vec: Learning distributed representations of code
Uri Alon, Meital Zilberstein, Omer Levy, and Eran Yahav · 2019
Closest in time.
Pathminer: a library for mining of path-based representations of code
Vladimir Kovalenko, Egor Bogomolov, Timofey Bryksin, and Alberto Bacchelli · 2019
Closest in time.
Code2seq: Generating sequences from structured representations of code
Shaked Brody Uri Alon, Omer Levy and Eran Yahav · 2019
Closest in time.
Neural program repair by jointly learning to localize and repair
Marko Vasic, Aditya Kanade, Petros Maniatis, David Bieber, and Rishabh Singh · 2019
Closest in time.
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