title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation | 2021 | EMNLP | Pretrain | Transformer | 📑 | ||
1 | TreeBERT: A Tree-Based Pre-Trained Model for Programming Language | 2021 | UAI | Pretrain | TreeBERT | 📑 | ||
2 | Code prediction by Feeding Trees to Transfomers | 2021 | ICSE | Code Generation | Transformer | 📑 | ||
3 | TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer | 2021 | ICML | Program Repair | Transformer | TFix's Code Patches Data | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | CodeGRU: Context-aware deep learning with gated recurrent unit for source code modeling | 2020 | IST | Code Generation | GRU | 📑 | ||
1 | A transformer-based approach for source code summarization | 2020 | ACL | Code Summarization | Transformer | 📑 | ||
2 | CodeBERT: A Pre-Trained Model for Programming and Natural Languages | 2020 | EMNLP | Pretrain | Transformer | 📑 | ||
3 | Learning and Evaluating Contextual Embedding of Source Code | 2020 | ICML | Pretrain | Transformer | 📑 | ||
4 | Deep Semantic Feature Learning for Software Defect Prediction | 2020 | TSE | Safety Analysis | DBN | 📑 | ||
5 | Modeling programs hierarchically with stack-augmented LSTM | 2020 | JSS | Code Generation | LSTM | C, python | 📑 | |
6 | Deep code comment generation with hybrid lexical and syntactical information | 2020 | FSE/EFEC | Code Summarization | GRU | 9714 Java projects from GitHub | 📑 | |
7 | Structural language models of code | 2020 | ICML | Code Generation | Transformer | 📑 | ||
8 | A self-attentional neural architecture for code completion with multi-task learning | 2020 | ICPC | Code Generation | Transformer | 📑 | ||
9 | Retrieval-based Neural Source Code Summarization | 2020 | ICSE | Code Summarization | Others | 📑 | ||
10 | Improving Code Search with Co-Attentive Representation Learning | 2020 | ICPC | Code Search | RNN | 📑 | ||
11 | Embedding Java Classes with code2vec: Improvements from Variable Obfuscation | 2020 | Program Classification | LSTM | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | Code2vec: learning distributed representations of code | 2019 | POPL | Code Generation | LSTM | 10072 Java GitHub repositories | 📑 | |
1 | Seml: A semantic lstm model for software defect prediction | 2019 | None | Safety Analysis | LSTM | 📑 | ||
2 | Code2seq: Generating Sequences from Structured Representations of Code | 2019 | ICLR | Code Generation | Bi-LSTM | Java, C#(dataset of CodeNN) | 📑 | |
3 | DeepCPDP: Deep Learning Based Cross-Project Defect Prediction | 2019 | Safety Analysis | Bi-LSTM | 📑 | |||
4 | Pythia: AI-assisted Code Completion System | 2019 | SIGKDD | Code Generation | Bi-LSTM | Python | 📑 | |
5 | A neural model for generating natural language summaries of program subroutines(astted-gru) | 2019 | ICSE | Code Summarization | GRU | 📑 | ||
6 | Neural Program Repair by Jointly Learning to Localize and Repair | 2019 | ICLR | Program Repair | LSTM | DeepFix | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | Neural Code Comprehension: A Learnable Representation of Code Semantics | 2018 | NuerIPs | Code representation | RNN | 📑 | ||
1 | A general path-based representation for predicting programproperties | 2018 | PLDL | Code Generation | word2vec,CRF | JavaScript, Java, Python, C# | 📑 | |
2 | Neural Code Completion | 2018 | ICPC | Code Generation | LSTM | JS150,PY150 | 📑 | |
3 | Code Completion with Neural Attention and Pointer Networks | 2018 | IJCAI | Code Generation | LSTM,pointer network | JS150,PY150 | 📑 | |
4 | Deep code comment generation | 2018 | ICPC | Code Summarization | LSTM | 📑 | ||
5 | Retrieval on Source Code: A Neural Code Search | 2018 | PLDI | Code Search | word embedding | 📑 | ||
6 | Deep code search | 2018 | ICSE | Code Search | RNN | 📑 | ||
7 | SCC: Automatic Classification of Code Snippets | 2018 | Program Classification | Multinomial Naive Bayes (MNB) | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | Exploring API embedding for API usages and applications | 2017 | ICSE | Code Generation | word2vec | Java, C# | 📑 | |
1 | Cclearner: A deep learning-based clone detection approach | 2017 | ICSME | Clone Detection | DNN | 📑 | ||
2 | Deep learning code fragments for code clone detection | 2017 | ASE | Clone Detection | RNN | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | A convolutional attention network for extreme summarization of source code | 2016 | ICML | Code Summarization | CAN | Java | 📑 | |
1 | A deep language model for software code | 2016 | None | Code Generation | LSTM | 📑 | ||
2 | Summarizing Source Code using a Neural Attention Model | 2016 | ACL | Code Summarization | LSTM | C# | 📑 | |
3 | Latent Attention For If-Then Program Synthesis | 2016 | NuerIPs | Code Generation | Bi-LSTM | 📑 | ||
4 | Abstract Syntax Networks for Code Generation and Semantic Parsing | 2016 | ACL | Code Generation | LSTM | 📑 | ||
5 | Automatically learning semantic features for defect prediction | 2016 | ICSE | Safety Analysis | DBN | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | On the localness of software | 2014 | FSE/ESEC | Code Generation | N-gram | 📑 | ||
1 | Phrase-Based Statistical Translation of Programming Languages | 2014 | OOPSLA | Code Generation | N-gram | 📑 | ||
2 | Code completion with statistical language models | 2014 | PLDI | Code Generation | RNN | 📑 |
title | year | venue | task | model | dataset | code | ||
---|---|---|---|---|---|---|---|---|
0 | On the naturalness of software | 2012 | None | Code Generation | N-gram | 📑 |