3 citations · 10 across the 12 of their papers we have counts for
5 papers · 1 filter
HotBugs.jar: A Benchmark of Hot Fixes for Time-Critical Bugs
Carol Hanna, Federica Sarro, Mark Harman +1
Hot fixes are urgent, unplanned changes deployed to production systems to address time-critical issues. Despite their importance, no existing evaluation benchmark focuses specifica…
Library Hallucinations in LLM-Generated Code: A Risk Analysis Grounded in Developer Queries
Lukas Twist, Mark Harman, Helen Yannakoudakis +1
Large language models (LLMs) now play a central role in code generation, yet they continue to hallucinate, frequently inventing non-existent libraries. Such library hallucinations…
Generative AI for Testing of Autonomous Driving Systems: A Survey
Qunying Song, He Ye, Mark Harman +1
Autonomous driving systems (ADS) have been an active area of research, with the potential to deliver significant benefits to society. However, before large-scale deployment on publ…
Benchmarking LLMs for Unit Test Generation from Real-World Functions
Dong Huang, Jie M. Zhang, Mark Harman +3
Recently, large language models (LLMs) have shown great promise in automating unit test generation, significantly reducing the manual effort required by developers. To effectively…
A Study of LLMs' Preferences for Libraries and Programming Languages
Lukas Twist, Mark Harman, Don Syme +4
Despite the rapid progress of large language models (LLMs) in code generation, existing evaluations focus on functional correctness or syntactic validity, overlooking how LLMs make…