14 citations · 29 across the 9 of their papers we have counts for
6 papers · 1 filter
CodeCureAgent: Automatic Classification and Repair of Static Analysis Warnings
Pascal Joos, Islem Bouzenia, Michael Pradel
Static analysis tools are widely used to detect bugs, vulnerabilities, and code smells. Traditionally, developers must resolve these warnings manually. Because this process is tedi…
LLM-Based Repair of Static Nullability Errors
Nima Karimipour, Pascal Joos, Michael Pradel +2
Modern Java projects increasingly adopt static analysis tools that prevent null-pointer exceptions by treating nullness as a type property. However, integrating such tools into lar…
Understanding Software Engineering Agents: A Study of Thought-Action-Result Trajectories
Islem Bouzenia, Michael Pradel
Large Language Model (LLM)-based agents are increasingly employed to automate complex software engineering tasks, such as program repair and issue resolution. These agents operate…
From Bugs to Benchmarks: A Comprehensive Survey of Software Defect Datasets
Hao-Nan Zhu, Robert M. Furth, Michael Pradel +1
Software defect datasets, which are collections of software bugs, are essential resources to facilitate empirical research and enable standardized benchmarking for a wide range of…
Issue2Test: Generating Reproducing Test Cases from Issue Reports
Noor Nashid, Islem Bouzenia, Michael Pradel +1
Automated tools for solving GitHub issues are receiving significant attention by both researchers and practitioners, e.g., in the form of foundation models and LLM-based agents pro…
Agentic AI Software Engineers: Programming with Trust
Abhik Roychoudhury, Corina Pasareanu, Michael Pradel +1
Large Language Models (LLMs) have shown surprising proficiency in generating code snippets, promising to automate large parts of software engineering via artificial intelligence (A…