Houari Sahraoui is a Professor in the GEODES Software Engineering Lab within the Department of Computer Science and Operations Research at the Université de Montréal. He also serves as Vice-Dean of the Faculty of Arts and Sciences. He received his Ph.D. in Computer Science from Pierre and Marie Curie University (LIP6) in 1995, specializing in Artificial Intelligence.

His research focuses on AI for Software Engineering, including software automation, model-driven engineering, digital twins, and the use of generative AI for code and modeling tasks. He has authored more than 200 publications in leading conferences and journals and has received numerous distinctions, including Best Paper Awards, ACM SIGSOFT Distinguished Paper Awards, and the IEEE TCSE 10-Year Most Influential Paper Award.

He has held several leadership positions within the software engineering community, including serving as General Chair of ASE, MODELS, and VISSOFT, Program Chair of MODELS and VISSOFT, and member of numerous IEEE and ACM conference program committees. He has also served as Associate Editor for several scientific journals, including Software and Systems Modeling, and is a founding member of CS-Can | Info-Can, the Canadian computer science society. He is a Fellow of Automated Software Engineering and the recipient of the CS-Can | Info-Can Lifetime Achievement Award in Computer Science.

Houari Sahraoui is a Professor in the GEODES Software Engineering Lab within the Department of Computer Science and Operations Research at the Université de Montréal since 1999. He served as Chair of the Department from 2013 to 2017 and is Vice-Dean of the Faculty of Arts and Sciences since 2017. He received his Ph.D. in Computer Science from Pierre and Marie Curie University (LIP6) in 1995, specializing in Artificial Intelligence.

Before joining the Université de Montréal, he worked as a researcher and later as a senior researcher at the Computer Research Institute of Montréal (CRIM). He has also held visiting professor positions at the University of Castilla-La Mancha in Spain and at INRIA Rennes in France.

2026

• Syntactic Multilingual Probing of Pre-Trained Language Models of Code (Journal of Systems and Software)
• MDE for Crop Representations in Smart Farming Digital Twins: A Reinforcement Learning Perspective (SoSyM)
• On the Utility of Domain Modeling Assistance with Large Language Models (TOSEM)
• Modeling Sampling Workflows for Code Repositories (MSR)
• Creativity Beyond Functionality: An Observational Study of Easter Eggs in Video Games (Games and Software Engineering Workshop)

2025

• Automation in Model-Driven Engineering: A Look Back, and Ahead (TOSEM)
• Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models (TOSEM)
• Combining Large Language Models with Static Analyzers for Code Review Generation (MSR)
• Harnessing Large Language Models for Curated Code Reviews (MSR)
• On the Challenges of Integrating Digital Twins (EDTconf)
• MONO2REST: Identifying and Exposing Microservices: A Reusable RESTification Approach (ICSR)
• Engineering Digital Twins for AI-Assisted Scientific Discovery: Case of Plasma-Enhanced Deposition (EDTconf)

2024

• CodeUltraFeedback: An LLM-as-a-Judge Dataset for Aligning Large Language Models to Coding Preferences (TOSEM)
• Improving Repair of Semantic ATL Errors Using a Social Diversity Metric (SoSyM)
• Building Domain-Specific Machine Learning Workflows: A Conceptual Framework for the State of the Practice (TOSEM)
• Improving the Learning of Code Review Successive Tasks with Cross-Task Knowledge Distillation (FSE, ACM SIGSOFT Distinguished Paper Award)
• A Modeling Methodology for Crop Representation in Digital Twins for Smart Farming (EDTconf)
• CodeLL: A Lifelong Learning Dataset to Support the Co-Evolution of Data and Language Models of Code (MSR)

2023

• Toward Optimal Psychological Functioning in AI-Driven Software Engineering Tasks (IEEE Software)
• Polyglot Software Development: Wait, What? (IEEE Software)
• MoTrans-BDI: Leveraging the Beliefs-Desires-Intentions Agent Architecture for Collaborative Model Transformation by Example (Journal of Computer Languages)
• Fingerprinting and Building Large Reproducible Datasets (ACM REP)
• Towards Using Few-Shot Prompt Learning for Automating Model Completion (ICSE NIER)
• Co-Simulation for Controlled Environment Agriculture (ANNSIM)
• On the Usage of Continual Learning for Out-of-Distribution Generalization in Pre-Trained Language Models of Code (ESEC/FSE)
• Digital Twins for Cyber-Biophysical Systems: Challenges and Lessons Learned (MODELS, Best Paper Award)
• A Multi-Step Learning Approach to Assist Code Review (SANER)

2022

• Promoting Social Diversity for the Automated Learning of Complex MDE Artefacts (SoSyM)
• Learning from Code Repositories to Recommend Model Classes (JOT)
• Recommending Metamodel Concepts during Modeling Activities with Pre-Trained Language Models (SoSyM)
• A Generic Approach to Detect Design Patterns in Model Transformations Using a String-Matching Algorithm (SoSyM)
• Better Modeling the Programming World with Code Concept Graphs-Augmented Multi-Modal Learning (ICSE NIER)
• Towards Automatically Extracting UML Class Diagrams from Natural Language Specifications (MDE Intelligence)
• Fine-Grained Analysis of Similar Code Snippets (ICSR)
• Fighting Evil Is Not Enough When Refactoring Metamodels: Promoting the Good Also Matters (SAC)
• Global Decision Making Over Deep Variability in Feedback-Driven Software Development (ASE NIER)
• AST-Probe: Recovering Abstract Syntax Trees from Hidden Representations of Pre-Trained Language Models (ASE)

2021

• A Hitchhiker’s Guide to Model-Driven Engineering for Data-Centric Systems (IEEE Software)
• Fixing Multiple Type Errors in Model Transformations with Alternative Oracles to Test Cases (JOT)
• Metamodel Refactoring Using Constraint Solving: A Quality-Based Perspective (SAM)
• Automated Patch Generation for Fixing Semantic Errors in ATL Transformation Rules (MODELS)
• Understanding High-Level Behavior with a Light-Traces Visualization Metaphor (VISSOFT)
• Checking Temporal Patterns of API Usage Without Code Execution (FormaliSE)

2020

• Towards Assisting Developers in API Usage by Automated Recovery of Complex Temporal Patterns (Information and Software Technology)
• Opportunities in Intelligent Modeling Assistance (SoSyM)
• ReSIde: Reusable Service Identification from Software Families (Journal of Systems and Software)