Grant: Alliance Grants
Brock University
$20,000.00
Leveraging Observability Via Tracing For Software Regression Detection and Root Cause Analysis
FY 2022-23
Summary
Execution tracing can provide valuable insights into the runtime behaviour of software systems. It can be used to detect, debug, analyze, and resolve a number of software problems, including memory leaks, latencies, network congestion, and security flaws. However, tracing can seriously degrade the system performance as it is difficult to produce a golden set of events possessing an optimal balance of minimal overhead, overlap, and redundancy while being precise enough to cover a wide range of problems. Providing software developers and testers with a small subset of key trace events and metrics can improve the design, testing, and debugging processes. Toward solving this challenge, Ciena, a telecom network equipment and software services supplier company, has partnered with a research group at Brock University to build and promote algorithms and tools for leveraging software observability through a cost-aware adaptive tracing model for software regression detection and analysis. This includes two sub-objectives. The first is to devise algorithms, strategies, and tools for the self-adaptive tracing of software systems. The second sub-objective focuses on root-cause analyses of latency changes detected by regression tests. This will include correlating changes in software behaviour with code blocks using traces collected at various levels of the system.The tools and methods provided by this research could be utilized by a wide range of companies in Canada to enhance the overall performance of their systems while reducing the time and costs of maintaining, monitoring, debugging, and tuning them. This is especially true for smaller companies lacking the resources to carry out a detailed analysis of their software solutions. This project will be primarily open-source and most results, tools, and contributions will be published and applied to open-source systems. Thus, apart from software companies, this work would directly benefit many industrial venues in Canada, including IT and phone companies, transportation, energy, and the research community in software engineering and telecommunications.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
572127-2022
Name nom
Ezzati Jivan, Naser NN
Department département
Computer Science
Organization id
22
Institution établissement
Brock University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2022
Award amount
20000
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
9999
Area of application group en
Not available
Area of application group fr
Non disponible
Area of application en
Not available
Area of application fr
Non disponible
Research subject code
2706
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Software engineering
Research subject fr
Génie logiciel
Installment
inst:1
Partie
1
Nb partie
1
Application title
Leveraging Observability Via Tracing For Software Regression Detection and Root Cause Analysis
Application summary
Execution tracing can provide valuable insights into the runtime behaviour of software systems. It can be used to detect, debug, analyze, and resolve a number of software problems, including memory leaks, latencies, network congestion, and security flaws. However, tracing can seriously degrade the system performance as it is difficult to produce a golden set of events possessing an optimal balance of minimal overhead, overlap, and redundancy while being precise enough to cover a wide range of problems. Providing software developers and testers with a small subset of key trace events and metrics can improve the design, testing, and debugging processes. Toward solving this challenge, Ciena, a telecom network equipment and software services supplier company, has partnered with a research group at Brock University to build and promote algorithms and tools for leveraging software observability through a cost-aware adaptive tracing model for software regression detection and analysis. This includes two sub-objectives. The first is to devise algorithms, strategies, and tools for the self-adaptive tracing of software systems. The second sub-objective focuses on root-cause analyses of latency changes detected by regression tests. This will include correlating changes in software behaviour with code blocks using traces collected at various levels of the system.The tools and methods provided by this research could be utilized by a wide range of companies in Canada to enhance the overall performance of their systems while reducing the time and costs of maintaining, monitoring, debugging, and tuning them. This is especially true for smaller companies lacking the resources to carry out a detailed analysis of their software solutions. This project will be primarily open-source and most results, tools, and contributions will be published and applied to open-source systems. Thus, apart from software companies, this work would directly benefit many industrial venues in Canada, including IT and phone companies, transportation, energy, and the research community in software engineering and telecommunications.
