Microsoft patents method to find new software bugs by comparing error logs
This filing describes a system that turns software error logs into mathematical vectors to capture their meaning. It compares these vectors from a new software version against older versions to spot new error patterns that didn't exist before, flagging them as regressions.
In the filing’s own words
A computerized method detects and mitigates regression errors in software services. Error log data associated with a current version of the service is obtained from a data store. The error log data is transformed into a first group of error log vectors using a model, wherein the first group of error log vectors represents semantic meaning of the error logs. A second group of error log vectors associated with a previous version of the service is obtained. Based on semantic similarity, the first group and the second group of error log vectors are clustered and, based on the clustering, a vector cluster that includes error log vectors from the first group and no error log vectors from the second group is identified as a regression vector cluster. Regression data associated with the regression vector cluster is generated and a regression mitigation action is performed using the generated regression data.
What exactly they claim (claim 1)
1. A system comprising: a processor; and a memory comprising computer program code, the memory and the computer program code configured to cause the processor to: obtain a runtime stack trace data batch associated with a current version of a service from a log store; transform the runtime stack trace data batch into a first group of error log vectors, wherein the first group of error log vectors represents a semantic meaning of a stack trace of the obtained runtime stack trace data batch associated with the current version of the service; obtain a second group of error log vectors associated with a previous version of the service from a historical vector store; based on semantic similarity, cluster the first group of error log vectors and the second group of error log vectors; based on the clustering, identify a vector cluster that includes an error log vector from the first group of error log vectors and no error log vector from the second group of error log vectors as a regression vector cluster; generate regression data associated with the regression vector cluster; and perform a regression mitigation action using the generated regression data.
Facts
- Company
- Microsoft (Microsoft Technology Licensing, LLC)
- Official title
- DETECTING SOFTWARE REGRESSIONS USING CLUSTERING OF SEMANTIC ERROR LOG VECTORS
- Publication number
- US20260329726A1
- Application number
- 19183747
- Filed
- Apr 18, 2025
- Published
- Oct 22, 2026
- Inventors
- 1
- Claims
- 20
Classified under
G06F 11/3636 Physics & computingG06F 11/3452 Physics & computingG06F 11/3476 Physics & computingMore from Microsoft in AI & software
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Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.