5 papers
LLM Code Smells: A Taxonomy and Detection Approach
Zacharie Chenail-Larcher, Brahim Mahmoudi, Naouel Moha +2
Large Language Models (LLMs) are increasingly integrated into software systems for diverse purposes, due to their versatility, flexibility, and ability to simulate human reasoning…
Specification and Detection of LLM Code Smells
Brahim Mahmoudi, Zacharie Chenail-Larcher, Naouel Moha +2
Large Language Models (LLMs) have gained massive popularity in recent years and are increasingly integrated into software systems for diverse purposes. However, poorly integrating…
GLiSE: A Prompt-Driven and ML-Powered Tool for Automated Grey Literature Extraction in Software Engineering
Houcine Abdelkader Cherief, Brahim Mahmoudi, Zacharie Chenail-Larcher +3
Grey literature is essential to software engineering research as it captures practices and decisions that rarely appear in academic venues. However, collecting and assessing it at…
SpecDetect4ML: Detecting Non-Local ML Code Smells with Code Property Graphs
Brahim Mahmoudi, Naouel Moha, Quentin Stiévenart +1
Machine Learning (ML) pipelines encode quality-relevant decisions across data preparation, training, evaluation, and configuration code. Some recurring source-level quality problem…
A Systematic Literature Review of Machine Learning Approaches for Migrating Monolithic Systems to Microservices
Imen Trabelsi, Brahim Mahmoudi, Jean Baptiste Minani +2
Scalability and maintainability challenges in monolithic systems have led to the adoption of microservices, which divide systems into smaller, independent services. However, migrat…