Mohammed Sayagh

Registered user since Tue 26 Sep 2017

Name:Mohammed Sayagh

I’m an assistant professor at Ecole Technologie Supérieur - Québec University. Before that, I was working as a PostDoc fellow in the Software Analysis and Intelligence Lab (SAIL) at Queen’s University (Kingston, ON) under the supervision of Prof. Ahmed E. Hassan. I obtained my Ph.D. from the Maintenance, Construction, and Intelligence of Software lab (MCIS) at Ecole Polytechnique (Montréal, QC) under the supervision of Prof. Bram Adams. I have a wide range of research interests that are related to software empirical studies. My main focus is related to software variability in multi-component software systems. I have applied different qualitative and quantitative empirical studies techniques to my research, such as mining software repositories (e.g., source code repositories, online forums, and DockerHub), source code analysis (e.g., Slicing), and machine learning.

Affiliation:ETS Montreal, University of Quebec
Personal website:
Research interests:Empirical Software Engineering, Mining Software Repositories, Distributed Systems, Configuration Management


MSR 2022 Committee Member in Program Committee within the Technical Papers-track
MSR 2021 Committee Member in Program Committee within the Technical Papers-track
ESEC/FSE 2021 Author of A Qualitative Study of the Benefits and Costs of Logging from Developers' Perspectives: A Journal First Presentation Proposal within the Journal First-track
ICSE 2021 Author of An Empirical Study of the Characteristics of Popular Minecraft Mods within the Journal-First Papers-track
Author of ConfigMiner: Identifying the Appropriate Configuration Options for Config-related User Questions by Mining Online Forums within the Journal-First Papers-track
SEAMS 2019 Committee Member in Artifact Program Committee within the SEAMS 2019-track
ICSE 2019 Author of Software Configuration Engineering in Practice - Interviews, Survey, and Systematic Literature Review within the Journal-First Papers-track
MSR 2018 Committee Member in Data Showcase Committe within the Data Showcase-track