Microsoft Technology Licensing, LLC

Eric M Borzello

Peter Alexi Gurevich

Yi-Lei Wu

Robert Novitskey

Anatoliy Burukhin

George Arthur Herbert, Iii

Athapan Arayasantiparb

Erik R Ashby

Jacob Richard Pitts

Larry Jack Israel

Huy Q Nguyen

Amit Dilip Ghosh

Eric Thomas Smith

Charles Marcus Reid, Iii

Kathleen R Kelly

Danny Thayer

Bruce Wiedeman

Mukunda Murthy

Bala Murali Loganath

Zhigiang Feng

Peter A Gurevich

Techniques and systems are described to improve computing device telemetry collection by automatic analysis and dynamic adjustment of telemetry collection rules. Certain implementations use a telemetry service to analyze telemetry messages and direct the adjusted rules at the client computing device, automatically and gradually refining telemetry collection as more relevant telemetry is received. Dynamic adjustments that can be made to the collection rules include, for example, changes to the collection frequency of telemetry messages, changes to the level of detail transmitted in the telemetry messages, and changes to the targets (e.g., applications, components, devices) from which to collect.

Dynamic telemetry message profiling and adjustment

A predictive contextual toolbar is presented that provides an identifiable region on which predicted commands can be surfaced. This user interface can be presented in cases where an indication of a request for a command (such as a formatting tool) is received, for example, while a user is interacting with a canvas of a productivity application. When conditions for surfacing a predictive command are met, the system can display an identifiable region on which predicted commands are surfaced according to context associated with the conditions for surfacing the predictive command. The identifiable region may be an extension of a mini toolbar. One or more dynamic predicted commands can be surfaced on the identifiable region to provide easily accessible, user specific, context related commands.

Predictive contextual toolbar for productivity applications

Technologies are generally described for collecting, analyzing and reporting telemetry data. A telemetry engine is built into a client application installed on a client device, and the telemetry engine is configured to collect and analyze application data at the client device and report the analyzed data to a service provider associated with the application. The telemetry application includes a specialized set of components, such as a telemetry transport component configured to communicate with the service provider, a data collection module configured to retrieve data from the application, and a rule manager and analyzer configured to analyze collected data according to a set of data collection rules provided by the service provider. The telemetry engine enables collection and analysis of telemetry data from multiple distributed client devices. The client devices dynamically change over time to ensure that current and important information is reported to the service provider.

Dynamic collection analysis and reporting of telemetry data

Techniques to automatically build a language dependency graph for localizable resources are described. A technique may include storing resources from a file in a translation database with data that indicates the language that the resource is in, the entity that created that version of the resource, and a dependency, if any, on a different language version of the resource. Subsequent translations of a resource may also be stored in the translation database in a manner that groups the translated version(s) of a resource to the original resource, and also stores the language of the resource, the entity that translated it, and the dependency to the language from which the resource was translated. A language dependency graph may be generated from the translation database for a file, where the graph reflects the languages of translation and dependency relationships among the translations. Other embodiments are described and claimed.

Techniques to automatically build a language dependency graph for localizable resources

In one embodiment, a computing device may compress a text file for storage by dynamically creating an encoding table. A storage device of the computing device may store an encoding table populated by string characters from a text file. A processor of the computing device may encode the text file by replacing a string character in a text string of the text file with a table index position of that string character in the encoding table. The processor of the computing device may decode the text file by replacing the table index position with the string character at the table index position in the encoding table.

Dynamic character encoding

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Redmond, WA, United States of America

Eric M Borzello