Microsoft Technology Licensing, LLC

Anjali Muralidhar

Arun Sacheti

Gaurang Prajapati

Daniel Marantz

Parthasarathy Govindarajen

Sebastian Kohlmeier

Krishnan Thazhathekalam

Aaron C Yuen

Darrin E Eide

Khalid Mahmood

Bartosz L Rakowski

Akshay Gandhi

James S Luke

In some embodiments, the disclosed subject matter involves a system and method relating to automation test runs of a software build, where the test runs effect impersonating an automation audience and selecting optional features to test with the automation audience. The automation audience is associated with a software build having static features, and the test runs include optional features, where each optional feature may have more than one associated treatment. Each feature/treatment combination may be tested in a test scenario associated with the feature/treatment combination. New features that are exposed in other audiences may be enabled for the automation audience to assist in verification and test of the new features. Dynamic selection of the optional features is effected using an application program interface (API) in the source code for the features, where the API accesses feature configuration information during runtime. Other embodiments are described and claimed.

Feature targeting of test automation lab machines

A query processing system (QPS) for generating query suggestions to a user by matching the user's input query against a set of query-detection grammars defined by respective rule modules, and with respect to a structured knowledge base. In response to the matching operation, the QPS may generate a set of synthetic query suggestions to the user, representing refinements of the user's input query. The QPS can also present a refinement tool that conveys refinement options to the user. The QPS may also present one or more preview items to the user upon the user's selection of one of the synthetic query suggestions. Each synthetic query suggestion and each preview item is guaranteed to having a matching counterpart information item in the structured knowledge base.

User interface mechanisms for query refinement

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Seattle, WA, United States of America

Anjali Muralidhar