All Stories

  1. Software Fairness: An Analysis and Survey
  2. A smarter tool to find security flaws in PHP websites before they go live
  3. AutoAdapt: On the Application of AutoML for Parameter-Efficient Fine-Tuning of Pre-Trained Code Models
  4. FuMi: A Runtime Fuzz-based Machine Learning Precision Measurement and Testing Framework
  5. Assessing the Robustness of Test Selection Methods for Deep Neural Networks
  6. The Importance of Accounting for Execution Failures when Predicting Test Flakiness
  7. Non-Flaky and Nearly-Optimal Time-based Treatment of Asynchronous Wait Web Tests
  8. Test Optimization in DNN Testing: A Survey
  9. SpecBCFuzz: Fuzzing LTL Solvers with Boundary Conditions
  10. Keeping Mutation Test Suites Consistent and Relevant with Long-Standing Mutants
  11. KAPE: Automatic performance estimation of deep code search
  12. Automated Repair of Unrealisable LTL Specifications Guided by Model Counting
  13. GraphPrior: Mutation-based Test Input Prioritization for Graph Neural Networks
  14. Evaluating the Impact of Experimental Assumptions in Automated Fault Localization
  15. iBiR : Bug Report driven Fault Injection
  16. GraphCode2Vec
  17. FlakiMe
  18. Improving machine translation systems via isotopic replacement
  19. Influence-driven data poisoning in graph-based semi-supervised classifiers
  20. Mutation Testing in Evolving Systems: Studying the relevance of mutants to code evolution
  21. An Empirical Study on Data Distribution-Aware Test Selection for Deep Learning Enhancement
  22. Test Selection for Deep Learning Systems
  23. Killing Stubborn Mutants with Symbolic Execution
  24. Search-based adversarial testing and improvement of constrained credit scoring systems
  25. Muteria
  26. Data-driven Simulation and Optimization for Covid-19 Exit Strategies
  27. The importance of accounting for real-world labelling when predicting software vulnerabilities
  28. Ukwikora: continuous inspection for keyword-driven testing
  29. Semantic fuzzing with zest
  30. Search-based test and improvement of machine-learning-based anomaly detection systems
  31. Are mutants really natural?
  32. Time to clean your test objectives
  33. Are mutation scores correlated with real fault detection?
  34. Featured model-based mutation analysis
  35. Comparing white-box and black-box test prioritization
  36. Employing second-order mutation for isolating first-order equivalent mutants
  37. A variability perspective of mutation analysis
  38. Metallaxis-FL: mutation-based fault localization