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LogAssist: Assisting Log Analysis Through Log Summarization

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LogAssist: Assisting Log Analysis Through Log Summarization

Locke, Steven ORCID: https://orcid.org/0000-0001-7401-2993 (2021) LogAssist: Assisting Log Analysis Through Log Summarization. Masters thesis, Concordia University.

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Abstract

Logs contain valuable information about the runtime behaviors of software systems. Thus, practitioners rely on logs for various tasks such as debugging, system comprehension, and anomaly detection. However, logs are difficult to analyze due to their unstructured nature and large size. In this thesis, we propose a novel approach called LogAssist that assists practitioners with log analysis. LogAssist provides an organized and concise view of logs by first grouping logs into event sequences (i.e., workflows), which better illustrate the system runtime execution paths. Then, LogAssist compresses the log events in workflows by hiding consecutive events and applying n-gram modeling to identify common event sequences. We evaluated LogAssist on logs generated by one enterprise and two open source systems. We find that LogAssist can reduce the number of log events that practitioners need to investigate by up to 99%. Through a user study with 19 participants, we find that LogAssist can assist practitioners by reducing the time required for log analysis tasks by an average of 40%. The participants also rated LogAssist an average of 4.53 out of 5 for improving their experiences of performing log analysis. Finally, we document our experiences and lessons learned from developing and adopting LogAssist in practice. We believe that LogAssist and our reported experiences may lay the basis for future analysis and interactive exploration on logs.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Computer Science and Software Engineering
Item Type:Thesis (Masters)
Authors:Locke, Steven
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Software Engineering
Date:9 August 2021
Thesis Supervisor(s):Chen, Tse-Hsun (Peter)
ID Code:988656
Deposited By: STEVEN LOCKE
Deposited On:29 Nov 2021 17:01
Last Modified:29 Nov 2021 17:01
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