5 papers
Disentangling Task Difficulty from Run-Level Failure in Agent Failure Prediction
Mohsen EsfandyariDoulabi, Lawrence Arkoh, Biruk Tadesse +4
Predicting whether an LLM agent will fail has emerged as a promising direction for supporting intervention during execution. Recent approaches report strong predictive performance,…
Where are the Hidden Gems? Applying Transformer Models for Design Discussion Detection
Lawrence Arkoh, Daniel Feitosa, Wesley K. G. Assunção
Design decisions are at the core of software engineering and appear in Q\&A forums, mailing lists, pull requests, issue trackers, and commit messages. Design discussions spanning a…
Secure or Suspect? Investigating Package Hallucinations of Shell Command in Original and Quantized LLMs
Md Nazmul Haque, Elizabeth Lin, Lawrence Arkoh +2
Large Language Models for code (LLMs4Code) are increasingly used to generate software artifacts, including library and package recommendations in languages such as Go. However, rec…
Relating Complexity, Explicitness, Effectiveness of Refactorings and Non-Functional Requirements: A Replication Study
Vinícius Soares, Lawrence Arkoh, Paulo Roberto Farah +3
Refactoring is a practice widely adopted during software maintenance and evolution. Due to its importance, there is extensive work on the effectiveness of refactoring in achieving…
Assessing the Bug-Proneness of Refactored Code: A Longitudinal Multi-Project Study
Isabella Ferreira, Lawrence Arkoh, Anderson Uchôa +3
Refactoring is a common practice in software development, aimed at improving the internal code structure in order to make it easier to understand and modify. Consequently, it is of…