Leveraging Observability via Tracing for Software Regression Detection and Root-cause Analysis

The main objective of the proposed research is to present a new adaptive tracing framework to dynamically adjust the monitoring and tracing of software systems according to the observability objectives at hand. This will lead to a more efficient and effective trace collection and will ensure that the proposed framework will efficiently collect just enough (cost-aware) and relevant (noise-free) trace data around the runtime issues. This is indeed crucial for Ciena, our partner company, where embedded systems and resource-constrained machines are heavily used. To achieve this objective, the interns will study and examine the existing methods and will devise algorithms and strategies for dynamic adaptive data collection as well as dynamic optimization of the amount, speed, and resolution of the collected data, based on the current ongoing behavior or the learned profile of the system under investigation.

Faculty Supervisor:

Naser Ezzati-Jivan

Student:

Partner:

Ciena Corporation (Ottawa, ON)

Discipline:

Computer science

Sector:

Information and cultural industries; Manufacturing; Professional, scientific and technical services

University:

Brock University

Program: