Abstract
Diagnosing software system failures from log data may involve the manual creation of a log pattern knowledge base and subsequent review of large log files. The disclosed technology provides systems and methods for artificial intelligence (AI)-driven root cause analysis. A component can programmatically scan source code to generate a structured knowledge base of log patterns and their associated context. An analysis component can then utilize this knowledge base to pre-filter relevant events from bug report logs. This curated and context-enriched log data can then be provided to a generative AI model to perform a root cause analysis. This approach can facilitate the automation of knowledge creation and log analysis, potentially reducing the manual effort involved in software debugging.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Malipatil, Avinash, "Artificial Intelligence Root Cause Analysis Using a Source Code-Derived Log Knowledge Base", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/9286