The Measurement, Observation, and Optimization of Software and its Evolution (MOOSE) lab is in the Department of Computer and Software Engineering, Polytechnique Montréal at Université de Montréal.

The mission of MOOSE is to help software engineers make their software systems more efficient and accurate. These software systems include traditional systems and emerging systems (e.g., AI-based systems and quantum-based systems). Three activities may contribute to the mission:

  • Measurement: Measuring the quality (e.g., performance efficiency) of software systems through statistic estimation (e.g., using performance models) or dynamic analysis (e.g., through performance testing or benchmarking).
  • Observation: Monitoring/Observing the runtime behaviors of software systems, including functional and non-functional behaviors (e.g., using logging/tracing). This can be achieved from two mutually complementary perspectives: 1) from the software development’s perspective, improving monitoring code and tools; 2) from the software operation’s perspective, improving the analytics and utilization of monitoring data.
  • Optimization: Recommending architecture/design/implementation alternatives to improve the quality of software systems.

Current members of MOOSE are performing research on the following topics:

  • AIOps (Artificial Intelligence for IT Operations)
  • Software monitoring (logging & log analytics)
  • Software performance engineering
  • AI engineering (focusing on the monitoring and performance aspects)
  • Quantum software engineering (focusing on the monitoring and performance aspects)
  • Mining software repositories
  • Software/hardware co-engineering

Current Members

Heng Li

Software monitoring, performance engineering, AIOps, mining software repositories, software quality engineering

Roozbeh Aghili

AIOps, software monitoring, software testing

Xingfang Wu

Log analytics, AIOps, mining software repositories, NLP

Kaveh Shahedi

Performance analytics, performance modelling, software tracing

Qiaolin (Isabelle) Qin

Data quality engineering, data anomaly detection

Ning Ma

Quantum software engineering; operations research

Forough Majidi

(Co-supervision with Prof. Foutse Khomh)
MLOps, AutoML, data/concept drift mitigation

Yang Liu

(Co-supervision with Prof. Foutse Khomh)
Robust AI for Code


Amin Ghadesi

Mining software repositories, AI engineering

Bhagya C

Mining software repositories, sports analytics, NLP

Vaibhav Ganatra

Quantum machine learning

Xiufan Li

Quantum software monitoring

Kun Che Tsai

ML system monitoring