All Stories

  1. It Takes Two to Tango: Accelerating Code Generation via Cache-Inspired Hierarchical Speculative Decoding
  2. Just Old Wine in a New Bottle: Improving Vulnerability Repair Robustness to Combat Homologous but Heterogeneous Vulnerabilities
  3. Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection
  4. One Size Does Fit All: Exploring Model Fusion for Software Engineering Tasks
  5. Coding in a Bubble? Evaluating LLMs in Resolving Context Adaptation Bugs during Code Adaptation
  6. Beyond Functional Correctness: A Knowledge-Enhanced Iterative Framework for Generating Criteria-Compliant Code
  7. Fault Localization from the Semantic Code Search Perspective
  8. EMSEdit: Efficient Multi-Step Meta-Learning-based Model Editing
  9. Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection
  10. Identifying Knowledge Editing Types in Large Language Models
  11. MiSum: Multi-modality Heterogeneous Code Graph Learning for Multi-intent Binary Code Summarization
  12. Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering
  13. Learning Feasible Causal Algorithmic Recourse: A Prior Structural Knowledge Free Approach
  14. Don’t Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems
  15. Divide-and-Conquer: Automating Code Revisions via Localization-and-Revision
  16. One Size Does Not Fit All: Multi-granularity Patch Generation for Better Automated Program Repair
  17. AutoRIC: Automated Neural Network Repairing Based on Constrained Optimization
  18. CAREER: Context-Aware API Recognition with Data Augmentation for API Knowledge Extraction
  19. When Neural Code Completion Models Size up the Situation: Attaining Cheaper and Faster Completion through Dynamic Model Inference
  20. Large Language Models are Few-Shot Summarizers: Multi-Intent Comment Generation via In-Context Learning
  21. An Extensive Study on Adversarial Attack against Pre-trained Models of Code
  22. Natural Language to Code: How Far Are We?
  23. CCT5: A Code-Change-Oriented Pre-trained Model
  24. Two Birds with One Stone: Boosting Code Generation and Code Search via a Generative Adversarial Network
  25. Pre-Implementation Method Name Prediction for Object-Oriented Programming
  26. Don't Complete It! Preventing Unhelpful Code Completion for Productive and Sustainable Neural Code Completion Systems
  27. Reentrancy Vulnerability Detection and Localization: A Deep Learning Based Two-phase Approach
  28. Is this Change the Answer to that Problem?
  29. Context-Aware Code Change Embedding for Better Patch Correctness Assessment
  30. Fine-grained code-comment semantic interaction analysis
  31. Lightweight global and local contexts guided method name recommendation with prior knowledge
  32. Automated patch correctness assessment
  33. On the efficiency of test suite based program repair