172 citations · 802 across the 171 of their papers we have counts for
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Tracing Hallucinations in LLM Reasoning for UML Class Diagram Generation: An Empirical Taxonomy and Mitigation Study
Mojdeh Rahmanian, Foutse Khomh, Ashkan Sami +1
Large Language Models (LLMs) can generate UML class diagrams from natural language requirements, but hallucinations may compromise the correctness and completeness of the resulting…
Revisiting Feedback-Driven LLM Code Repair: A Replication and Exploratory Java Extension
Louis Lalonde, Wassim Keddache, Thomas Perron Touchette +2
Since the advent of Large Language Models (LLMs), practitioners have increasingly leveraged them to support their software engineering tasks, including automated code repair, showi…
LLM Serving in the Wild: An Empirical Study of Frameworks, Methods, and System Designs
Forough Majidi, Mohammad Mehdi Morovati, Foutse Khomh +1
Large Language Models (LLMs) are integrated into software systems and AI services, making efficient LLM serving a concern for software engineering. Serving LLMs is challenging beca…
How Do AI Coding Agents Contribute to Software Development? an Empirical Study of Agentic Pull Requests
Iren Mazloomzadeh, Mohammad Mehdi Morovati, Foutse Khomh
Recent advances in large language models and their rapid adoption across software engineering tasks have made Artificial Intelligence (AI) coding agents an integral component of mo…
GitHub Template Repositories: Served Domains, Maintenance, and Practitioner Guidelines
Leuson Da Silva, Altaf Allah Abbassi, Imen Trabelsi +2
Over time, GitHub has introduced different strategies for sharing reusable code artifacts. In addition to fork-based reuse, template repositories provide a distinct feature for gen…
An Empirical Study on Logging Evolution On Stack Overflow: Trends, Topics, and Challenges
Patrick Loic Foalem, Andre Nguimbous, Foutse Khomh +2
Context: Logging is a crucial practice in software engineering, aiding developers in debugging applications when errors occur. While existing research has explored logging challeng…
A Research Agenda on Agents and Software Engineering: Outcomes from the Rio A2SE Seminar
Davide Taibi, Henry Muccini, Karthik Vaidhyanathan +15
The rise of agentic AI is reshaping software engineering in two intertwined directions: agents are increasingly applied to support software engineering tasks, and Agentic AI system…
On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies
Ali Soltanian Fard Jahromi, Amjed Tahir, Peng Liang +1
The security of AI-generated code remains a major obstacle to its widespread adoption. Although code generation models achieve strong performance on functional benchmarks, their ou…
Mitigating False Positives in Static Memory Safety Analysis of Rust Programs via Reinforcement Learning
Akilesh P, Leuson Da Silva, Foutse Khomh +1
Static analysis tools are essential for ensuring memory safety in Rust programs, particularly as Rust gains adoption in safety-critical domains. However, existing tools such as Rud…
Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code
Yang Liu, Da Song, Armstrong Foundjem +2
Chain-of-Thought (CoT) prompting is widely used to elicit explicit reasoning from large language models for code (LLM4Code). However, its impact on robustness and the stability of…
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
Logging plays a central role in ensuring reproducibility, observability, and reliability in machine learning (ML) systems. While logging is generally considered a good engineering…
Dynasto: Validity-Aware Dynamic-Static Parameter Optimization for Autonomous Driving Testing
Dmytro Humeniuk, Mohammad Hamdaqa, Houssem Ben Braiek +2
Extensive simulation-based testing is important for assuring the safety of autonomous driving systems (ADS). However, generating safety-critical traffic scenarios remains challengi…
QUARE: Quality-Aware Requirements Analysis through Multi-Agent Dialectical Negotiation
Haowei Cheng, Milhan Kim, Foutse Khomh +4
Automating requirements quality analysis remains challenging because multiple, often conflicting quality attributes must be balanced while preserving stakeholder intent. Existing L…
Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes
Mehil B Shah, Mohammad Mehdi Morovati, Mohammad Masudur Rahman +1
Agentic AI systems combine LLM-based reasoning, orchestration, tool invocation, and interaction with external environments. These systems introduce faults that are difficult to cha…
Real Faults in Model Context Protocol (MCP) Software: a Comprehensive Taxonomy
Mina Taraghi, Mohammad Mehdi Morovati, Foutse Khomh
The rapid adoption of foundation models has significantly expanded the capabilities of software systems, enabling them to perform complex language, reasoning, and interaction tasks…
Improving the Robustness of Large Language Models for Code Tasks via Fine-tuning with Perturbed Data
Yang Liu, Armstrong Foundjem, Xingfang Wu +2
Context: In the fast-paced evolution of software development, Large Language Models (LLMs) have become indispensable tools for tasks such as code generation, completion, analysis,…
Tracing Stereotypes in Pre-trained Transformers: From Biased Neurons to Fairer Models
Gianmario Voria, Moses Openja, Foutse Khomh +2
The advent of transformer-based language models has reshaped how AI systems process and generate text. In software engineering (SE), these models now support diverse activities, ac…
An Empirical Study of Policy-as-Code Adoption in Open-Source Software Projects
Patrick Loic Foalem, Foutse Khomh, Leuson Da Silva +1
\textbf{Context:} Policy-as-Code (PaC) has become a foundational approach for embedding governance, compliance, and security requirements directly into software systems. While orga…
Empirical Characterization of Logging Smells in Machine Learning Code
Patrick Loic Foalem, Leuson Da Silva, Foutse Khomh +2
\underline{Context:} Logging is a fundamental yet complex practice in software engineering, essential for monitoring, debugging, and auditing software systems. With the increasing…
QMon: Monitoring the Execution of Quantum Circuits with Mid-Circuit Measurement and Reset
Ning Ma, Jianjun Zhao, Foutse Khomh +2
Unlike classical software, where logging and runtime tracing can effectively reveal internal execution status, quantum circuits possess unique properties, such as the no-cloning th…
A Survey of Bugs in AI-Generated Code
Ruofan Gao, Amjed Tahir, Peng Liang +2
Developers are widely using AI code-generation models, aiming to increase productivity and efficiency. However, there are also quality concerns regarding the AI-generated code. The…
Imitation Game: Reproducing Deep Learning Bugs Leveraging an Intelligent Agent
Mehil B Shah, Mohammad Masudur Rahman, Foutse Khomh
Despite their wide adoption in various domains (e.g., healthcare, finance, software engineering), Deep Learning (DL)-based applications suffer from many bugs, failures, and vulnera…
RefAgent: A Multi-agent LLM-based Framework for Automatic Software Refactoring
Khouloud Oueslati, Maxime Lamothe, Foutse Khomh
Large Language Models (LLMs) have substantially influenced various software engineering tasks. Indeed, in the case of software refactoring, traditional LLMs have shown the ability…
Refactoring with LLMs: Bridging Human Expertise and Machine Understanding
Yonnel Chen Kuang Piao, Jean Carlors Paul, Leuson Da Silva +3
Code refactoring is a fundamental software engineering practice aimed at improving code quality and maintainability. Despite its importance, developers often neglect refactoring du…