Leveraging Observability Via Tracing For Software Regression Detection and Root Cause Analysis
Leveraging Observability Via Tracing For Software Regression Detection and Root Cause Analysis
批准号:
572127-2022
负责人:
EzzatiJivan, NaserNN
金额:
$1.46万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31
中文摘要
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英文摘要
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.
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