title:HAConvGNN: Hierarchical Attention Based Convolutional Graph Neural Network for Code Documentation Generation in Jupyter Notebooks year: 2021 venue: EMNLP task: Code Summarization model: HAConvGNN dataset: notebookcdg pdf: https://arxiv.org/abs/2104.01002 code: https://github.com/xuyeliu/HAConvGNN
title:Code Completion by Modeling Flattened Abstract Syntax Trees as Graphs year: 2021 venue: AAAI task: Code Generation model: GAT dataset: JS150, PY150 pdf: http://arxiv.org/abs/2103.09499 code:
title: CAST: Enhancing Code Summarization with Hierarchical Splitting and Reconstruction of Abstract Syntax Trees year: 2021 venue: EMNLP task: Code Summarization model: RNN,attention dataset: TL-CodeSum pdf: http://arxiv.org/abs/2108.12987 code: https://anonymous.4open.science/r/CAST/
title: Learning to represent programs with graphs year: 2018 venue: ICLR task: Defect Prediction,Code Generation model: GGNN dataset: iclr18-prog-graphs-dataset pdf: https://arxiv.org/abs/1711.00740 code: https://github.com/Microsoft/gated-graph-neural-network-samples
title: A Novel Neural Source Code Representation Based on Abstract Syntax Tree year: 2019 venue: ICSE task: Program Classification, Clone Detection model: bidirectional RNN dataset: OJClone,BCB pdf: https://www.semanticscholar.org/paper/1432c8378b1cafa3f91f09fa743082d154fdab92 code: https://github.com/zhangj1994/astnn
title: TBCNN: A tree-based convolutional neural network for programming language processing year: 2014 venue: arixiv task: Program Classification model: TBCNN dataset: OJClone pdf: https://arxiv.org/abs/1409.5718v1 code: https://sites.google.com/site/treebasedcnn/
title: Capturing Source Code Semantics via Tree-based Convolution over API-enhanced AST year: 2019 venue: ACM International Conference on Computing Frontiers task: Clone Detection,Code Search, Code Summarization model: tree-based LSTM dataset:OJClone,BigCloneBench pdf: https://doi.org/10.1145/3310273.3321560 code: https://github.com/milkfan/TBCAA
title: Improving automatic source code summarization via deep reinforcement learning year: 2018 venue: ASE task: Code Summarization model: RNN,Tree-RNN dataset: code-comment pairs pdf: https://arxiv.org/abs/1811.07234v1 code:
title: CODIT: Code Editing with Tree-Based Neural Models year: 2020 venue: IEEE Transactions on Software Engineering task: Program Repair model: LSTM dataset: Defects4J,Code-Change-Data pdf: http://arxiv.org/abs/1810.00314 code: https://git.io/JJGwU
title: Gated graph sequence neural networks year: 2015 venue: ICLR task: Program Verification model: GGNN dataset: program variables dataset produced in this work pdf: http://arxiv.org/abs/1511.05493 code: https://github.com/yujiali/ggnn
title: Structured neural summarization year: 2019 venue: ICLR task: Code Summarization model: GGNN dataset: C# dataset,JAVA method naming datasets, Python method documentation dataset pdf: https://arxiv.org/abs/1811.01824v4 code: https://github.com/CoderPat/structured-neural-summarization
title: GGF: A graph-based method for programming language syntax error correction year: 2020 venue: ICPC task: Program Repair model: GGNN dataset: DeepFix dataset,CodeForces dataset pdf: https://dl.acm.org/doi/10.1145/3387904.3389252 code:
title: Improved code summarization via a graph neural network year: 2020 venue: ICPC task: Code Summarization model: ConvGNN dataset: Java method-comment pairs pdf: https://arxiv.org/abs/2004.02843v2 code:
title: Code Clone Detection with Hierarchical Attentive Graph Embedding year: 2021 venue: International Journal of Software Engineering and Knowledge Engineering task: Clone Detection model: GCN dataset: IJDataset2.0 pdf: https://www.worldscientific.com/doi/abs/10.1142/S021819402150025X code:
title: Graph-based, Self-Supervised Program Repair from Diagnostic Feedback year: 2020 venue: ICML task: Program Repair model: GAT, LSTM dataset: SPoC pdf: http://arxiv.org/abs/2005.10636 code: https://github.com/michiyasunaga/DrRepair
title: Generative code modeling with graphs year: 2019 venue: ICLR task: Program Repair,Code Generation model: GRU,GGNN dataset: C# dataset pdf: https://arxiv.org/abs/1805.08490v2 code: https://github.com/Microsoft/graph-based-code-modelling
title: Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting year: 2021 venue: ICPC task: Code Summarization model: Tree-LSTM dataset: CodeSearchNet, Hybrid-DeepCom Dataset pdf: https://arxiv.org/abs/2103.07845v2 code: https://github.com/XMUDM/BASTS
title: Neural network-based graph embedding for cross-platform binary code similarity detection year: 2017 venue: Proceedings of the ACM Conference on Computer and Communications Security task: Program Repair model: Structure2vec dataset: collected in this work, Genius Dataset pdf: http://arxiv.org/abs/1708.06525 code: https://github.com/xiaojunxu/dnn-binary-code-similarity
title: BugGraph: Differentiating Source-Binary Code Similarity with Graph Triplet-Loss Network year: 2021 venue: ASIA CCS task: Vulnerability Detection model: GTN dataset: Validation dataset, Syntax similar dataset, ARM binary dataset, Firmware image dataset pdf: https://www2.seas.gwu.edu/~howie/publications/BugGraph-ASIACCS21.pdf code:
title: DeepBinDiff: Learning Program-Wide Code Representations for Binary Diffing year: 2020 venue: NDSS task: Clone Detection model: Text-associated DeepWalk dataset: Coreutils, Diffutils, Findutils pdf: https://dx.doi.org/10.14722/ndss.2020.24311 code: https://github.com/deepbindiff/DeepBinDiff
title: Order matters: Semantic-aware neural networks for binary code similarity detection year: 2020 venue: AAAI task: Clone Detection model: MPNN,CNN dataset: gcc dataset pdf: https://ojs.aaai.org/index.php/AAAI/article/view/5466 code:
title: Learning semantic program embeddings with graph interval neural network year: 2020 venue: Proceedings of the ACM on Programming Languages task: Program Repair model: GINN dataset: PY150 pdf: https://arxiv.org/abs/2005.09997v2 code:
title: Classifying Malware Represented as Control Flow Graphs using Deep Graph Convolutional Neural Network year: 2019 venue:Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN task: Defect Prediction model: DGCNN dataset: MSKCFG Dataset, YANCFG Dataset pdf: https://ieeexplore.ieee.org/document/8809504 code:
title: Semantic Code Clone Detection Via Event Embedding Tree and GAT Network year: 2020 venue: QRS task: Clone Detection model: Transformer, GAT, CNN dataset: OJClone pdf: https://ieeexplore.ieee.org/document/9282778/ code: https://github.com/lbzwoaini/CSEM.git
title: How could Neural Networks understand Programs? year: 2021 venue: ICML task: Clone Detection model: Transformer dataset: OJClone pdf: http://arxiv.org/abs/2105.04297 code: https://github.com/pdlan/OSCAR
title: Multi-modal attention network learning for semantic source code retrieval year: 2019 venue: ASE task: Code Search model: GGNN, Tree-LSTM dataset: C dataset pdf: https://arxiv.org/abs/1909.13516v1 code:
title: Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks year: 2019 venue: NIPS task: Vulnerability Detection model: GGNN, GRU, CNN dataset: Devign Dataset pdf: https://arxiv.org/abs/1909.03496v1 code: https://sites.google.com/view/devign
title:Flow2Vec:value-flow-based precise code embedding year: 2020 venue: Proceedings of the ACM on Program ming Languages task: Code Summarization, Program Classification model: Flow2Vec dataset: C Dataset pdf: https://dl.acm.org/doi/abs/10.1145/3428301 code:
title:Compiler-based graph representations for deep learning models of code year: 2020 venue: Proceedings of the 29th International Conference on Compiler Construction task: Program Classification model: GGNN dataset: OpenCL Dataset pdf: https://doi.org/10.1145/3377555.3377894 code: https:ithub.com/tud-ccc/learning-compiler-graphs
title: DeepSim: Deep Learning Code Functional Similarity year: 2018 venue: ESEC/FSE task: Clone Detection model: Feed-forward neural network dataset: Google Code Jam (GCJ), BigCloneBench pdf: https://doi.org/10.1145/3236024.3236068 code: https://github.com/parasol-aser/deepsim
title: CoCoSum: Contextual Code Summarization with Multi-Relational Graph Neural Network year: 2021 venue: arxiv task: Code Summarization model: Transformer,Multi-Relational Graph Neural Network dataset: CodeSearchNet, CoCoNet pdf: https://arxiv.org/abs/2107.01933v1 code:
title: Improving bug detection via context-based code representation learning and attention-based neural networks year: 2019 venue: Proceedings of the ACM on Programming Languages task: Defect Prediction model: GRU, CNN, Attention mechanism dataset: Java Dataset collected in this work pdf: https://dl.acm.org/doi/abs/10.1145/3360588 code:
title: Modeling and discovering vulnerabilities with code property graphs year: 2014 venue: Proceedings IEEE Symposium on Security and Privacy task: Vulnerability Detection model: code property graphs dataset: Linux kernel's code collected in this work pdf: http://ieeexplore.ieee.org/document/6956589/ code:
title: Retrieval-Augmented Generation for Code Summarization via Hybrid GNN year: 2021 venue: ICLR task: Code Summarization model: GNN dataset: C Program Dataset pdf: https://arxiv.org/abs/2006.05405v5 code: https://github.com/shangqing-liu/CCSD-benchmark-for-code-summarization
title: Probabilistic model for code with decision trees year: 2016 venue: SIGPLAN task: Code Generation model: Decision tree dataset: PY150, JS150 pdf: https://dl.acm.org/doi/10.1145/2983990.2984041 code:
title: Open vocabulary learning on source code with a graph-structured caches year: 2019 venue: ICML task: Code Generation model: MPNN,CharCNN dataset: Java repos collected in this work pdf: https://arxiv.org/abs/1810.08305v2 code: https://github.com/mwcvitkovic/Deep_Learning_On_Code_With_A_Graph_Vocabulary