Abstract

Issue tracking systems are widely issued for managing the reporting and addressing of various issues in a software system. In many cases, determining the specific software components connected to the issue and the appropriate persons to resolve the issue is not straightforward and requires a series of assignments until the right components and persons are assigned to understand and resolve the issue. The techniques of this disclosure employ a machine learning model trained on existing labeled data from an issue tracking system to automate the process of assigning appropriate components to issues and routing them to personnel most suitable for handling them. Additionally, the model allocates a priority for each issue and reroutes issues in case the initial allocation fails to resolve the issue within reasonable time.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

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