All Stories

  1. Hot Fixing Software: A Comprehensive Review of Terminology, Techniques, and Applications
  2. It Is Giving Major Satisfaction: Why Fairness Matters for Software Practitioners
  3. Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
  4. Greening AI-enabled Systems with Software Engineering: A Research Agenda for Environmentally Sustainable AI Practices
  5. LLM-Based Misconfiguration Detection for AWS Serverless Computing
  6. Behind the Hot Fix: Demystifying Hot Fixing Industrial Practices at Zühlke and Beyond
  7. Enhanced Fairness Testing via Generating Effective Initial Individual Discriminatory Instances
  8. Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software
  9. SCOPE : Performance Testing for Serverless Computing
  10. Bias Behind the Wheel: Fairness Testing of Autonomous Driving Systems
  11. Game Software Engineering: A Controlled Experiment Comparing Automated Content Generation Techniques
  12. Broken Agreement: The Evolution of Solidity Error Handling
  13. Understanding Fairness in Software Engineering: Insights from Stack Exchange Sites
  14. Exploring LLM-Driven Explanations for Quantum Algorithms
  15. Enhancing Energy-Awareness in Deep Learning through Fine-Grained Energy Measurement
  16. Speeding up Genetic Improvement via Regression Test Selection
  17. The Patch Overfitting Problem in Automated Program Repair: Practical Magnitude and a Baseline for Realistic Benchmarking
  18. Bias Mitigation for Machine Learning Classifiers: A Comprehensive Survey
  19. Fairness Testing: A Comprehensive Survey and Analysis of Trends
  20. TrickyBugs: A Dataset of Corner-case Bugs in Plausible Programs
  21. Greenlight: Highlighting TensorFlow APIs Energy Footprint
  22. User-Centric Deployment of Automated Program Repair at Bloomberg
  23. Fairness Improvement with Multiple Protected Attributes: How Far Are We?
  24. Assess and Summarize: Improve Outage Understanding with Large Language Models
  25. MEG: Multi-objective Ensemble Generation for Software Defect Prediction (HOP GECCO'23)
  26. Multi-objective Search for Gender-fair and Semantically Correct Word Embeddings (HOP GECCO'23)
  27. Who Judges the Judge: An Empirical Study on Online Judge Tests
  28. Automated Optimisation of Modern Software System Properties
  29. A Comprehensive Empirical Study of Bias Mitigation Methods for Machine Learning Classifiers
  30. MAAT: a novel ensemble approach to addressing fairness and performance bugs for machine learning software
  31. On the Relationship Between Story Points and Development Effort in Agile Open-Source Software
  32. MEG: Multi-objective Ensemble Generation for Software Defect Prediction
  33. On the use of evaluation measures for defect prediction studies
  34. Py2Cy
  35. A versatile dataset of agile open source software projects
  36. Green AI
  37. Privileged and unprivileged groups
  38. Did You Do Your Homework? Raising Awareness on Software Fairness and Discrimination
  39. Diversifying Focused Testing for Unit Testing
  40. Fairea: a model behaviour mutation approach to benchmarking bias mitigation methods
  41. The effect of offspring population size on NSGA-II
  42. Enhancing Genetic Improvement of Software with Regression Test Selection
  43. Artifact for Enhancing Genetic Improvement of Software with Regression Test Selection
  44. FrUITeR: a framework for evaluating UI test reuse
  45. A new approach to distribute MOEA pareto front computation
  46. Optimising word embeddings with search-based approaches
  47. The importance of accounting for real-world labelling when predicting software vulnerabilities
  48. Some challenges for software testing research (invited talk paper)
  49. Comparing the effectiveness of three parallelisation approaches for genetic algorithms
  50. Linear Programming as a Baseline for Software Effort Estimation
  51. Multi-objective software effort estimation
  52. A parallel genetic algorithms framework based on Hadoop MapReduce
  53. Exploiting prior-phase effort data to estimate the effort for the subsequent phases
  54. The plastic surgery hypothesis