Microsoft Technology Licensing, LLC

Brian T Klamik

Leonardo Esteban Blanco

Silvana Patricia Moncayo

Max Alan McMullen

Michael I Borysenko

Daniel Wood

Keith D Melmon

Allison Klein

Michael P Crider

Craig C Peeper

Michael A Toelle

Bruce Lydell Nelson

Sam Glassenberg

Buffer display techniques are described. In one or more implementations, at least part of an off-screen buffer is rasterized by an application to generate an item for display by the computing device. One or more communications are formed that describe the part of the off-screen buffer which contains the item that is to be copied to update an onscreen buffer.

Buffer display techniques

Systems and methods that optimize GPU processing by front loading activities from a set time/binding time to creation time via enhancements to an API that configures the GPU. Such enhancements to the API include: implementing layering arrangements, employing state objects and view components for data objects; incorporating a pipeline stage linkage/signature, employing a detection mechanism to mitigate error conditions. Such an arrangement enables front loading of the work and reduction of associated API calls.

Application program interface for programmable graphics pipeline

Sampled profile data provides information about processor activity during a test. Processor activity can be analyzed to determine an amount of processor resources used to execute the various functions, modules, and processes associated with a tested software activity. Statistical methods can be applied to the resource data from multiple test runs to determine whether a significant regression has occurred between a baseline test pass and a daily test pass. By collecting data at the function, module and process levels, significant regressions may be uncovered at any of the levels. Regressions may also be ranked according to their importance, which allows for identification and notification of development teams responsible for significant regressions.

Statistical analysis of sampled profile data in the identification of significant software test performance regressions

In testing hardware and/or software, processor events can be logged during a test. Using the events, we can determine an amount of processor activity not used to execute software considered to be involved in the test. Such noise may then be accounted for in determining and prioritizing regressions, as well as to improve test results generally.

Noise accommodation in hardware and software testing

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Brian T Klamik