For attending the papers' presentation, see the conference program here.
- Learning Probabilistic Models for Static Analysis Alarms
- DeepTraLog: Trace-Log Combined Microservice Anomaly Detection through Graph-based Deep Learning
- Unleashing the Power of Compiler Intermediate Representation to Enhance Neural Program Embeddings
- TOGA: A Neural Method for Test Oracle Generation
- Automated Detection of Password Leakage from Public GitHub Repositories
- Log-based Anomaly Detection with Deep Learning: How Far Are We
- Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for Python
- VarCLR: Variable Semantic Representation Pre-training via Contrastive Learning
- Detecting False Alarms from Automatic Static Analysis Tools: How Far are We?
- Improving Fault Localization and Program Repair with Deep Semantic Features and Transferred Knowledge
- NPEX: Repairing Java Null Pointer Exceptions without Tests
- Neural Program Repair using Execution-based Backpropagation
- DeepSTL - From English Requirements to Signal Temporal Logic
- Learning to Recommend Method Names with Global Context
- CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences
- Nalin: Learning from Runtime Behavior to Find Name-Value Inconsistencies
- Practical Automated Detection of Malicious npm Packages
- What Do They Capture? - A Structural Analysis of Pre-Trained Language Models for Source Code
- Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
- On the Evaluation of Neural Code Summarization
- FIRA: Fine-Grained Graph-Based Code Change Representation for Automated Commit Message Generation
- Striking a Balance: Pruning False-Positives from Static Call Graphs
- Data-Driven Loop Bound Learning for Termination Analysis
- CLEAR: Contrastive Learning for API Recommendation
- DeepFD: Automated Fault Diagnosis and Localization for Deep Learning Programs
- Fast Changeset-based Bug Localization with BERT
- Multilingual training for Software Engineering
- AutoTransform: Automated Code Transformation to Support Modern Code Review Process
- MVD: Memory-related Vulnerability Detection Based on Flow-Sensitive Graph Neural Networks
- VulCNN: An Image-inspired Scalable Vulnerability Detection System
- Using Deep Learning to Generate Complete Log Statements
- Cross-Domain Deep Code Search with Few-Shot Learning
- DeepAnalyze: Learning to Localize Crashes at Scale
- Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding
- ARCLIN: Automated API Mention Resolution for Unformatted Texts
- Using Reinforcement Learning for Load Testing of Video Games
- Using Pre-Trained Models to Boost Code Review Automation
- Jigsaw: Large Language Models meet Program Synthesis
- Recommending Good First Issues in GitHub OSS Projects
- DEAR: A Novel Deep Learning-based Approach for Automated Program Repair
- AST-Trans: Code Summarization with Efficient Tree-Structured Attention
- SPT-Code: Sequence-to-Sequence Pre-Training for Learning Representation of Source Code
- A Universal Data Augmentation Approach for Fault Localization
- Automated Assertion Generation via Information Retrieval and Its Integration with Deep Learning
- Manas: Mining Software Repositories to Assist AutoML