| 0 |
On the naturalness of software |
2012 |
None |
Code Generation |
N-gram |
|
📑 |
|
| 1 |
On the localness of software |
2014 |
FSE/ESEC |
Code Generation |
N-gram |
|
📑 |
|
| 2 |
Phrase-Based Statistical Translation of Programming Languages |
2014 |
OOPSLA |
Code Generation |
N-gram |
|
📑 |
|
| 3 |
A convolutional attention network for extreme summarization of source code |
2016 |
ICML |
Code Summarization |
CAN |
Java |
📑 |
 |
| 4 |
Code completion with statistical language models |
2014 |
PLDI |
Code Generation |
RNN |
|
📑 |
|
| 5 |
Neural Code Comprehension: A Learnable Representation of Code Semantics |
2018 |
NuerIPs |
Code representation |
RNN |
|
📑 |
|
| 6 |
A deep language model for software code |
2016 |
None |
Code Generation |
LSTM |
|
📑 |
|
| 7 |
Summarizing Source Code using a Neural Attention Model |
2016 |
ACL |
Code Summarization |
LSTM |
C# |
📑 |
 |
| 8 |
Latent Attention For If-Then Program Synthesis |
2016 |
NuerIPs |
Code Generation |
Bi-LSTM |
|
📑 |
|
| 9 |
Abstract Syntax Networks for Code Generation and Semantic Parsing |
2016 |
ACL |
Code Generation |
LSTM |
|
📑 |
|
| 10 |
CodeGRU: Context-aware deep learning with gated recurrent unit for source code modeling |
2020 |
IST |
Code Generation |
GRU |
|
📑 |
|
| 11 |
A transformer-based approach for source code summarization |
2020 |
ACL |
Code Summarization |
Transformer |
|
📑 |
 |
| 12 |
CodeBERT: A Pre-Trained Model for Programming and Natural Languages |
2020 |
EMNLP |
Pretrain |
Transformer |
|
📑 |
 |
| 13 |
Learning and Evaluating Contextual Embedding of Source Code |
2020 |
ICML |
Pretrain |
Transformer |
|
📑 |
|
| 14 |
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation |
2021 |
EMNLP |
Pretrain |
Transformer |
|
📑 |
|
| 15 |
A general path-based representation for predicting programproperties |
2018 |
PLDL |
Code Generation |
word2vec,CRF |
JavaScript, Java, Python, C# |
📑 |
|
| 16 |
Exploring API embedding for API usages and applications |
2017 |
ICSE |
Code Generation |
word2vec |
Java, C# |
📑 |
|
| 17 |
Automatically learning semantic features for defect prediction |
2016 |
ICSE |
Safety Analysis |
DBN |
|
📑 |
|
| 18 |
Deep Semantic Feature Learning for Software Defect Prediction |
2020 |
TSE |
Safety Analysis |
DBN |
|
📑 |
|
| 19 |
Neural Code Completion |
2018 |
ICPC |
Code Generation |
LSTM |
JS150,PY150 |
📑 |
|
| 20 |
Code Completion with Neural Attention and Pointer Networks |
2018 |
IJCAI |
Code Generation |
LSTM,pointer network |
JS150,PY150 |
📑 |
 |
| 21 |
Deep code comment generation |
2018 |
ICPC |
Code Summarization |
LSTM |
|
📑 |
 |
| 22 |
Code2vec: learning distributed representations of code |
2019 |
POPL |
Code Generation |
LSTM |
10072 Java GitHub repositories |
📑 |
 |
| 23 |
Seml: A semantic lstm model for software defect prediction |
2019 |
None |
Safety Analysis |
LSTM |
|
📑 |
|
| 24 |
Modeling programs hierarchically with stack-augmented LSTM |
2020 |
JSS |
Code Generation |
LSTM |
C, python |
📑 |
|
| 25 |
Code2seq: Generating Sequences from Structured Representations of Code |
2019 |
ICLR |
Code Generation |
Bi-LSTM |
Java, C#(dataset of CodeNN) |
📑 |
 |
| 26 |
DeepCPDP: Deep Learning Based Cross-Project Defect Prediction |
2019 |
|
Safety Analysis |
Bi-LSTM |
|
📑 |
|
| 27 |
Pythia: AI-assisted Code Completion System |
2019 |
SIGKDD |
Code Generation |
Bi-LSTM |
Python |
📑 |
 |
| 28 |
A neural model for generating natural language summaries of program subroutines(astted-gru) |
2019 |
ICSE |
Code Summarization |
GRU |
|
📑 |
 |
| 29 |
Deep code comment generation with hybrid lexical and syntactical information |
2020 |
FSE/EFEC |
Code Summarization |
GRU |
9714 Java projects from GitHub |
📑 |
 |
| 30 |
TreeBERT: A Tree-Based Pre-Trained Model for Programming Language |
2021 |
UAI |
Pretrain |
TreeBERT |
|
📑 |
 |
| 31 |
Structural language models of code |
2020 |
ICML |
Code Generation |
Transformer |
|
📑 |
|
| 32 |
Code prediction by Feeding Trees to Transfomers |
2021 |
ICSE |
Code Generation |
Transformer |
|
📑 |
|
| 33 |
A self-attentional neural architecture for code completion with multi-task learning |
2020 |
ICPC |
Code Generation |
Transformer |
|
📑 |
|
| 34 |
Retrieval-based Neural Source Code Summarization |
2020 |
ICSE |
Code Summarization |
Others |
|
📑 |
|
| 35 |
Retrieval on Source Code: A Neural Code Search |
2018 |
PLDI |
Code Search |
word embedding |
|
📑 |
|
| 36 |
Deep code search |
2018 |
ICSE |
Code Search |
RNN |
|
📑 |
|
| 37 |
Improving Code Search with Co-Attentive Representation Learning |
2020 |
ICPC |
Code Search |
RNN |
|
📑 |
|
| 38 |
Cclearner: A deep learning-based clone detection approach |
2017 |
ICSME |
Clone Detection |
DNN |
|
📑 |
|
| 39 |
Deep learning code fragments for code clone detection |
2017 |
ASE |
Clone Detection |
RNN |
|
📑 |
|
| 40 |
Neural Program Repair by Jointly Learning to Localize and Repair |
2019 |
ICLR |
Program Repair |
LSTM |
DeepFix |
📑 |
 |
| 41 |
TFix: Learning to Fix Coding Errors with a Text-to-Text Transformer |
2021 |
ICML |
Program Repair |
Transformer |
TFix's Code Patches Data |
📑 |
 |
| 42 |
Embedding Java Classes with code2vec: Improvements from Variable Obfuscation |
2020 |
|
Program Classification |
LSTM |
|
📑 |
 |
| 43 |
SCC: Automatic Classification of Code Snippets |
2018 |
|
Program Classification |
Multinomial Naive Bayes (MNB) |
|
📑 |
 |