Abstract

As consumer devices age and on-device software modules get updated, it can become difficult to trap quality problems and determine prevalence and severity of respective problems. This disclosure describes techniques to perform on-device diagnostics pertaining to a particular issue. Queries are sent to devices in the field and responses are received that include information about the existence and attributes of a bug/issue. The devices run the queries on respective on-device logs and report back the requested information in a privacy-preserving manner. The prevalence and severity of the issue, which are major deciding factors in rolling out a fix, can be determined by aggregating the received responses.

Creative Commons License

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

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