A survey on automated log analysis for reliability engineering
Logs are semi-structured text generated by logging statements in software source code. In
recent decades, software logs have become imperative in the reliability assurance …
recent decades, software logs have become imperative in the reliability assurance …
Engineering ai systems: A research agenda
Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in
industry. However, based on well over a dozen case studies, we have learned that …
industry. However, based on well over a dozen case studies, we have learned that …
What's wrong with computational notebooks? Pain points, needs, and design opportunities
S Chattopadhyay, I Prasad, AZ Henley… - Proceedings of the …, 2020 - dl.acm.org
Computational notebooks-such as Azure, Databricks, and Jupyter-are a popular, interactive
paradigm for data scientists to author code, analyze data, and interleave visualizations, all …
paradigm for data scientists to author code, analyze data, and interleave visualizations, all …
Logram: Efficient Log Parsing Using -Gram Dictionaries
Software systems usually record important runtime information in their logs. Logs help
practitioners understand system runtime behaviors and diagnose field failures. As logs are …
practitioners understand system runtime behaviors and diagnose field failures. As logs are …
Identifying impactful service system problems via log analysis
Logs are often used for troubleshooting in large-scale software systems. For a cloud-based
online system that provides 24/7 service, a huge number of logs could be generated every …
online system that provides 24/7 service, a huge number of logs could be generated every …
The evolution of continuous experimentation in software product development: from data to a data-driven organization at scale
Software development companies are increasingly aiming to become data-driven by trying
to continuously experiment with the products used by their customers. Although familiar with …
to continuously experiment with the products used by their customers. Although familiar with …
Characterizing the natural language descriptions in software logging statements
Logging is a common programming practice of great importance in modern software
development, because software logs have been widely used in various software …
development, because software logs have been widely used in various software …
A qualitative study of the benefits and costs of logging from developers' perspectives
Software developers insert logging statements in their source code to collect important
runtime information of software systems. In practice, logging appropriately is a challenge for …
runtime information of software systems. In practice, logging appropriately is a challenge for …
An improved KNN-based efficient log anomaly detection method with automatically labeled samples
S Ying, B Wang, L Wang, Q Li, Y Zhao… - ACM Transactions on …, 2021 - dl.acm.org
Logs that record system abnormal states (anomaly logs) can be regarded as outliers, and
the k-Nearest Neighbor (kNN) algorithm has relatively high accuracy in outlier detection …
the k-Nearest Neighbor (kNN) algorithm has relatively high accuracy in outlier detection …
Characterizing and detecting anti-patterns in the logging code
Snippets of logging code are output statements (eg, LOG. info or System. out. println) that
developers insert into a software system. Although more logging code can provide more …
developers insert into a software system. Although more logging code can provide more …