Dear SEMTLers,
You are cordially invited to the thesis defence of Oussama Ben Sghaier scheduled on Thursday, June 26, 9:30, Room 1140, Pav. André Aisenstadt
Title
Empowering Code Review Automation: A Data-Centric, Multi-Task-Driven, and Human-Aware Approach
Abstract
The integration of artificial intelligence, particularly large language models (LLMs), has transformed software engineering by enabling new levels of automation for tasks like code review—crucial yet time-consuming and complex. While traditional tools relied on rule-based static analyzers, LLMs now make it possible to generate review comments similar to those written by humans. However, fully automating this task remains challenging due to rigid analyzers, isolated modeling of interdependent code review subtasks, low-quality of the code review training data, and the used evaluation metrics that neglect human aspects.
This thesis tackles these issues through four contributions: (1) a multi-step learning framework for identifying review issues; (2) a unified architecture jointly modeling comment generation, code refinement, and quality estimation (3) a data curation pipeline using LLMs to improve comment quality; and (4) a human-centered evaluation framework that accounts for developer well-being. Together, these advances pave the way for intelligent, reliable, and human-aligned code review assistants.
Jury
Bram Adams
Michalis Famelis
Jean-François Godbout
Philippe Langlais
Houari Sahraoui
Houari Sahraoui
Professeur, Dép. d'informatique et de RO
Professor, Dep. of Computer Science and OR
Vice-doyen à la planification, aux infrastructures et à l'ÉDI
Vice-dean, planning, infrastructure, and EDI
Faculté des arts et des sciences
Université de Montréal