Mohammed Sayagh

Office A-2420

Département de génie logiciel et des TI

Research interests:

  • Information and Communications Technologies

Research areas:

  • Empirical software engineering
  • Configuration management
  • DevOps
  • Software monitoring and AIOps
  • Mining software repositories
  • Multi-component software systems
Publications: article

Publications: article

Publications: article

Publications: article

Courses and support services


LOG680 Introduction à l'approche DevOps (Fall 2022)
MGL869 Sujets spéciaux I : génie logiciel (Fall 2022)
LOG680 Introduction à l'approche DevOps (Winter 2022)

Assistance to students

Mémoire à 30 crédits

    Co-directed by: Sayagh, Mohammed
    Extraction and Analysis of Behavior Practices Based on GitLab MR Information, by Mashari,Seyedbehnam.
    Winter 2022

    Co-directed by: Sayagh, Mohammed
    Utilisation des flux de valeur pour l’optimisation des processus DevOps, by Legault,Julien.
    Summer 2022

Projet d'application à 15 crédits

    La taille des images de Docker - État de pratique et aide à l’optimisation des images, by Haloui,Khalid.
    Fall 2022

Thèse de doctorat (recherche appliquée)

    Co-directed by: Sayagh, Mohammed
    On the support of Web-based Software Systems Maintenance and Evolution, by Bessghaier,Narjes.
    Fall 2022

Peer-reviewed article published in a refereed journal (4)

Youssef Esseddiq Ouatiti, Mohammed Sayagh, Noureddine Kerzazi, Ahmed E. Hassan. 2022. « An empirical study on log level prediction for multi-component systems ». IEEE Transactions on Software Engineering. (In press)

Kundi Yao, Mohammed Sayagh, Weiyi Shang, Ahmed E. Hassan. 2022. « Improving state-of-the-art compression techniques for log management tools ». IEEE Transactions on Software Engineering. vol. 48 , nº 8. p. 2748-2760.

Md Hasan Ibrahim, Mohammed Sayagh, Ahmed E. Hassan. 2021. « A study of how Docker Compose is used to compose multi-component systems ». Empirical Software Engineering. vol. 26 , nº 6.

Yingzhe Lyu, Heng Li, Mohammed Sayagh, Zhen Ming Jiang, Ahmed E. Hassan. 2021. « An empirical study of the impact of data splitting decisions on the performance of AIOps solutions ». ACM Transactions on Software Engineering and Methodology. vol. 30 , nº 4.

Awards and honors