All Stories

  1. Optimizing Search-Based Unit Test Generation with Large Language Models: An Empirical Study
  2. Risky Dynamic Typing-related Practices in Python: An Empirical Study
  3. Knowledge Graph Driven Inference Testing for Question Answering Software
  4. Generating Python Type Annotations from Type Inference: How Far Are We?
  5. Assessing effectiveness of test suites: what do we know and what should we do?
  6. Towards Better Dependency Scope Settings in Maven Projects
  7. Back Deduction Based Testing for Word Sense Disambiguation Ability of Machine Translation Systems
  8. Code-line-level bugginess identification: How far have we come, and how far have we yet to go?
  9. Accelerating OCR-Based Widget Localization for Test Automation of GUI Applications
  10. Training data debugging for the fairness of machine learning software
  11. Mutant reduction evaluation: what is there and what is missing?
  12. How Far Have We Progressed in Identifying Self-admitted Technical Debts? A Comprehensive Empirical Study
  13. Measuring Discrimination to Boost Comparative Testing for Multiple Deep Learning Models
  14. Stay professional and efficient
  15. Multiple-boundary clustering and prioritization to promote neural network retraining
  16. An Empirical Study on Dynamic Typing Related Practices in Python Systems
  17. An Empirical Study on Critical Blocking Bugs
  18. RoScript
  19. Impact analysis of cross-project bugs on software ecosystems
  20. How C++ Templates Are Used for Generic Programming
  21. Python probabilistic type inference with natural language support