activity
20242026
most citedRepairAgent: An Autonomous, LLM-Based Agent for Program Repair

14 citations · 29 across the 9 of their papers we have counts for

collaborators

11 papers

cs.SE2026

Prefactory: Automated Discovery and Application of Library-Adoption Refactorings

Islem Bouzenia, Michael Pradel

Replacing hand-written code with library API calls is a common refactoring that can reduce code size, make code more idiomatic, and reuse well-tested implementations. Yet many libr…

cs.SE2026

Evaluating LLM Agents on Automated Software Analysis Tasks

Islem Bouzenia, Cristian Cadar, Michael Pradel

Numerous software analysis tools exist today, yet applying them to diverse open-source projects remains challenging due to environment setup, dependency resolution, and analysis to…

cs.SE2025

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…

cs.SE2025

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…

cs.SE2025★ 2 cited

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…

cs.SE2025

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…

cs.SE2025

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…

cs.SE2025★ 2 cited

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…

cs.SE2024★ 2 cited

You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary Projects

Islem Bouzenia, Michael Pradel

The ability to execute the test suite of a project is essential in many scenarios, e.g., to assess code quality and code coverage, to validate code changes made by developers or au…

cs.SE2024★ 14 cited

RepairAgent: An Autonomous, LLM-Based Agent for Program Repair

Islem Bouzenia, Premkumar Devanbu, Michael Pradel

Automated program repair has emerged as a powerful technique to mitigate the impact of software bugs on system reliability and user experience. This paper introduces RepairAgent, t…

cs.SE2024★ 9 cited

DyPyBench: A Benchmark of Executable Python Software

Islem Bouzenia, Bajaj Piyush Krishan, Michael Pradel

Python has emerged as one of the most popular programming languages, extensively utilized in domains such as machine learning, data analysis, and web applications. Python's dynamic…