Abstract: In non-limiting examples of the present disclosure, systems and methods are described that relate to providing, in a browser environment, a sidebar search capability to users. Once in a primary content page, the user is able to select text for searching. In response, the system provides a context menu or keyboard shortcut that includes an option for conducting a sidebar search. In response to user selection, the system passes highlighted or selected text as a parameter to the search engine. The results are provided in an area alongside the currently displayed content page, such as in a sidebar search pane. The user is able to experience search results without leaving the context of their current search tab.

Abstract: In some embodiments, the disclosed subject matter involves a system and method relating to segmenting user population to test the quality of different software states. In at least one embodiment, the software states may be exposed dynamically to users who receive a software build, because features may be turned on/off via the server, at runtime. In an embodiment, if the server is unavailable, feature information may be retrieved from the local client storage. New features may be dynamically exposed to segments of a population to assist in verification and test of the new features. Other embodiments are described and claimed.

Abstract: 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 audience and selecting optional features to test with the impersonated audience. The impersonated 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 may be dynamically exposed to a selected audience to assist in verification and test of the new features. Other embodiments are described and claimed.

Abstract: A machine may be configured to test an application based on an in-app impersonating of an audience profile. For example, the machine receives a selection of an audience identifier via a user interface. The machine maps the audience identifier to a configuration file that includes identifiers of features of the application available for use by the audience. The machine, based on the audience identifier and the configuration file, causes a display, in the user interface, of the identifiers of the features. The machine receives, via the user interface, a request to modify an operational state of a feature of the application in the software context associated with the audience. The machine configures, at run-time, the application based on the audience identifier, the configuration file, and the request to modify the operational state of the feature. The configuring results in the application including the feature in a modified operational state.

Abstract: 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.

Abstract: 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.

Abstract: 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.