Learning to Represent Programs with Graphs

1 November 2017

Papers citing "Learning to Represent Programs with Graphs"

50 / 122 papers shown

Title
Productivity, Portability, Performance: Data-Centric Python Yiheng Wang Yao Zhang Yanzhang Wang Yan Wan Jiao Wang Zhongyuan Wu Yuhao Yang Bowen She 54 94 0 01 Jul 2021
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns Susheel Suresh Vinith Budde Jennifer Neville Pan Li Jianzhu Ma 32 131 0 11 Jun 2021
Understanding Neural Code Intelligence Through Program Simplification Md Rafiqul Islam Rabin Vincent J. Hellendoorn Mohammad Amin Alipour AAML 49 58 0 07 Jun 2021
How Attentive are Graph Attention Networks? Shaked Brody Uri Alon Eran Yahav GNN 52 1,016 0 30 May 2021
Self-Supervised Bug Detection and Repair Miltiadis Allamanis Henry Jackson-Flux Marc Brockschmidt 13 103 0 26 May 2021
DeepDebug: Fixing Python Bugs Using Stack Traces, Backtranslation, and Code Skeletons Dawn Drain Colin B. Clement Guillermo Serrato Neel Sundaresan 17 31 0 19 May 2021
How could Neural Networks understand Programs? Dinglan Peng Shuxin Zheng Yatao Li Guolin Ke Di He Tie-Yan Liu NAI 18 61 0 10 May 2021
Toward Code Generation: A Survey and Lessons from Semantic Parsing Celine Lee Justin Emile Gottschlich Dan Roth Intel Labs 3DV 28 15 0 26 Apr 2021
GraphTheta: A Distributed Graph Neural Network Learning System With Flexible Training Strategy Yongchao Liu Houyi Li Guowei Zhang Xintan Zeng Yongyong Li ... Peng Zhang Zhao Li Kefeng Deng Changhua He Wenguang Chen GNN 44 11 0 21 Apr 2021
Code Structure Guided Transformer for Source Code Summarization Shuzheng Gao Cuiyun Gao Yulan He Jichuan Zeng L. Nie Xin Xia Michael R. Lyu 22 96 0 19 Apr 2021
Evaluating Pre-Trained Models for User Feedback Analysis in Software Engineering: A Study on Classification of App-Reviews M. Hadi Fatemeh H. Fard 15 30 0 12 Apr 2021
Do We Need Anisotropic Graph Neural Networks? Shyam A. Tailor Felix L. Opolka Pietro Lio Nicholas D. Lane 43 34 0 03 Apr 2021
PSIMiner: A Tool for Mining Rich Abstract Syntax Trees from Code Egor Spirin Egor Bogomolov V. Kovalenko T. Bryksin 33 15 0 23 Mar 2021
Project-Level Encoding for Neural Source Code Summarization of Subroutines Aakash Bansal S. Haque Collin McMillan 14 48 0 22 Mar 2021
Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs Yanlin Wang Hui Li 10 85 0 17 Mar 2021
Learning to Make Compiler Optimizations More Effective Rahim Mammadli Marija Selakovic F. Wolf Michael Pradel 21 13 0 24 Feb 2021
DOBF: A Deobfuscation Pre-Training Objective for Programming Languages Baptiste Roziere Marie-Anne Lachaux Marc Szafraniec Guillaume Lample AI4CE 52 137 0 15 Feb 2021
Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks Yujun Yan Milad Hashemi Kevin Swersky Yaoqing Yang Danai Koutra 36 248 0 12 Feb 2021
Learning Structural Edits via Incremental Tree Transformations Ziyu Yao Frank F. Xu Pengcheng Yin Huan Sun Graham Neubig CLL 154 27 0 28 Jan 2021
Code Summarization with Structure-induced Transformer Hongqiu Wu Hai Zhao Min Zhang 41 84 0 29 Dec 2020
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 25 115 0 16 Dec 2020
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity Kexin Pei Zhou Xuan Junfeng Yang Suman Jana Baishakhi Ray 19 88 0 16 Dec 2020
InferCode: Self-Supervised Learning of Code Representations by Predicting Subtrees Nghi D. Q. Bui Yijun Yu Lingxiao Jiang SSL 44 104 0 13 Dec 2020
Learning to Represent Programs with Heterogeneous Graphs Kechi Zhang Wenhan Wang Huangzhao Zhang Ge Li Zhi Jin GNN 21 63 0 08 Dec 2020
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization Sahil Suneja Yunhui Zheng Yufan Zhuang Jim Laredo Alessandro Morari AAML 32 32 0 25 Nov 2020
Neural Software Analysis Michael Pradel S. Chandra NAI 21 31 0 16 Nov 2020
Pointing to Subwords for Generating Function Names in Source Code Shogo Fujita Hidetaka Kamigaito Hiroya Takamura Manabu Okumura 11 2 0 09 Nov 2020
Deep Graph Matching and Searching for Semantic Code Retrieval Xiang Ling Lingfei Wu Sai-gang Wang Gaoning Pan Tengfei Ma Fangli Xu A. Liu Chunming Wu S. Ji GNN 33 91 0 24 Oct 2020
Learning to Execute Programs with Instruction Pointer Attention Graph Neural Networks David Bieber Charles Sutton Hugo Larochelle Daniel Tarlow GNN 19 43 0 23 Oct 2020
GraphCodeBERT: Pre-training Code Representations with Data Flow Daya Guo Shuo Ren Shuai Lu Zhangyin Feng Duyu Tang ... Dawn Drain Neel Sundaresan Jian Yin Daxin Jiang M. Zhou 73 1,094 0 17 Sep 2020
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research Cody Watson Nathan Cooper David Nader-Palacio Kevin Moran Denys Poshyvanyk 26 111 0 14 Sep 2020
Static Neural Compiler Optimization via Deep Reinforcement Learning Rahim Mammadli Ali Jannesari F. Wolf 28 30 0 20 Aug 2020
On the Generalizability of Neural Program Models with respect to Semantic-Preserving Program Transformations Md Rafiqul Islam Rabin Nghi D. Q. Bui Ke Wang Yijun Yu Lingxiao Jiang Mohammad Amin Alipour 30 90 0 31 Jul 2020
CoreGen: Contextualized Code Representation Learning for Commit Message Generation L. Nie Cuiyun Gao Zhicong Zhong Wai Lam Yang Liu Zenglin Xu 21 46 0 14 Jul 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 44 147 0 13 Jul 2020
Retrieval-Augmented Generation for Code Summarization via Hybrid GNN Shangqing Liu Yu Chen Xiaofei Xie J. Siow Yang Liu 23 163 0 09 Jun 2020
On the Bottleneck of Graph Neural Networks and its Practical Implications Uri Alon Eran Yahav GNN 32 661 0 09 Jun 2020
A Structural Model for Contextual Code Changes Shaked Brody Uri Alon Eran Yahav KELM 19 7 0 27 May 2020
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback Michihiro Yasunaga Percy Liang LRM 24 171 0 20 May 2020
Geometric graphs from data to aid classification tasks with graph convolutional networks Yifan Qian P. Expert P. Panzarasa Mauricio Barahona GNN 25 9 0 08 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 30 2,652 0 02 May 2020
Typilus: Neural Type Hints Miltiadis Allamanis Earl T. Barr Soline Ducousso Zheng Gao 16 130 0 06 Apr 2020
OptTyper: Probabilistic Type Inference by Optimising Logical and Natural Constraints Irene Vlassi Pandi Earl T. Barr Andrew D. Gordon Charles Sutton 22 29 0 01 Apr 2020
Code Prediction by Feeding Trees to Transformers Seohyun Kim Jinman Zhao Yuchi Tian S. Chandra 35 216 0 30 Mar 2020
ProGraML: Graph-based Deep Learning for Program Optimization and Analysis Chris Cummins Zacharias V. Fisches Tal Ben-Nun Torsten Hoefler Hugh Leather 88 56 0 23 Mar 2020
Incorporating Relational Background Knowledge into Reinforcement Learning via Differentiable Inductive Logic Programming Ali Payani Faramarz Fekri 21 18 0 23 Mar 2020
A Toolkit for Generating Code Knowledge Graphs Ibrahim Abdelaziz Julian T Dolby Jamie McCusker Kavitha Srinivas 13 24 0 21 Feb 2020
Detecting Code Clones with Graph Neural Networkand Flow-Augmented Abstract Syntax Tree Wenhan Wang Ge Li Bo Ma Xin Xia Zhi Jin GNN 18 250 0 20 Feb 2020
Equivalence of Dataflow Graphs via Rewrite Rules Using a Graph-to-Sequence Neural Model Steve Kommrusch Théo Barollet L. Pouchet 24 6 0 17 Feb 2020
Adversarial Robustness for Code Pavol Bielik Martin Vechev AAML 19 89 0 11 Feb 2020