Microsoft Technology Licensing, LLC

Alexander S Weil

Igor B Peev

Gary Caldwell

Stephen C Rowe

Steven Marcel Elza Wilssens

Xiaoyu Chai

Satish Kumar Shetty

Connie Qin Yang

Tomas Aleksas Mereckis

Eamon Guthrie Cosgrove Millman

Soheil Sadeghi

Omari Carter-thorpe

Disclosed herein is a system for leveraging telemetry data representing usage of a component installed on a group of sampled computing devices to confidently infer the quality of a user experience and/or the behavior of the component (e.g., an operating system) on a larger group of unsampled computing devices. The system is configured to use a propensity score matching approach to identify a sampled computing device that best represents an unsampled computing device using configuration data that is collected from both the sampled and unsampled computing devices. The quality of the user experience and/or the behavior of the component may be captured by a metric of interest (e.g., a QoS value). Accordingly, the system is configured to use the known metric of interest, determined from the telemetry data collected for the sampled computing device, to determine or predict the metric of interest for the unsampled computing device.

Using propensity score matching to determine metric of interest for unsampled computing devices

A technology for reporting diagnostic information for code of an application program interface is disclosed. In one method approach, diagnostic information for a line of code in a file associated with an application program interface is received. The diagnostic information includes a designation of the line of code. The diagnostic information is stored in a fixed sized buffer. Efficient use of memory is provided without requiring elimination of other diagnostic information previously stored in the fixed sized buffer.

Reporting diagnostic information for code of an application program interface

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Redmond, WA, United States of America

Alexander S Weil