"自动日志解析工具与基准研究"

This paper discusses the importance of logs in software development and maintenance, as they provide crucial runtime information for monitoring systems and identifying abnormal behaviors and errors. However, with the growing scale and complexity of modern software systems, the sheer volume of logs has become overwhelming, making manual log inspection impractical in many cases. To address this challenge, automated log parsing tools and benchmarks have been developed to streamline the process of log analysis. These tools use machine learning and natural language processing techniques to automatically extract relevant information from logs, saving time and effort for developers and support engineers. The paper presents a translation of the research paper "Tools and Benchmarks for Automated Log Parsing," which explores the capabilities of these automated tools in efficiently parsing logs and evaluating their performance. The study highlights the various techniques and algorithms used in the development of these tools, as well as the benchmarks used to assess their accuracy and efficiency. Overall, the research underscores the significance of automated log parsing tools in modern software development and maintenance, providing a more efficient and effective way to deal with the increasing volume and complexity of logs in software systems. Automated log parsing tools not only save time and effort for developers but also improve the overall system monitoring and error detection capabilities.