Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Techniques are described for sampling across trusted and untrusted distributed components. In accordance with embodiments, a first computing device receives a request from a second computing device, the first request including an operation identifier (ID) and a sampling ID that was generated by transforming a telemetry scope ID from a first value in a first domain to a second value in a second domain. The transformation may serve to anonymize and compress the telemetry scope ID. The first computing device determines whether or not to sample by comparing a ratio between the sampling ID and a size of the second domain with a sampling rate associated with the first computing device. The first computing device records telemetry about its processing of the first request in response to determining to sample and does not record any telemetry about its processing of the first request in response to determining not to sample.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.

Abstract: The present invention extends to methods, systems, and computer program products for identifying impacted tests from statically collected data. In general, static dependency data, possibly augmented with some dynamic data, is used to find an appropriate set of impacted tests for code changes. In some embodiments, static dependency analysis is used to identify tests impacted by a code change. Heuristics can be used to assist with identifying an appropriate set of impacted tests to run for a code change. Dynamic data can be used to augment static dependency data to identify more optimal sets of impacted tests to run for a code change.

Abstract: Tools and techniques assist developers with the detection of memory leaks by using correlation of data type memory usage trends. In particular, investigations of memory leaks can be prioritized without always resorting to the use of bulky and performance-degrading memory dumps, by using these tools and techniques to identify leaky correlated data types. Data about a program's memory usage is processed to identify memory usage trends over time for respective data types, and the trends are searched for significant correlations. Correlated trends (and hence their corresponding data types) are grouped. Memory usage analysis information is displayed for grouped data types, such as the names of the most rapidly leaking data types, the names of correlated data types, leak rates, and leak amounts in terms of memory size and/or data object counts. Memory usage data may also be correlated with processing load requests to indicate which requests have associated memory leaks.

Abstract: The present invention extends to methods, systems, and computer program products for identifying impacted tests from statically collected data. In general, static dependency data, possibly augmented with some dynamic data, is used to find an appropriate set of impacted tests for code changes. In some embodiments, static dependency analysis is used to identify tests impacted by a code change. Heuristics can be used to assist with identifying an appropriate set of impacted tests to run for a code change. Dynamic data can be used to augment static dependency data to identify more optimal sets of impacted tests to run for a code change.

Abstract: A sequence of user actions is generated from a runtime trace of a client application that is analyzed against a set of detectors to infer a feature-level usage analytic. The feature-level usage analytic identifies a common trait among the various users that use a feature of the application and is used as a basis to reflect the user's experience with the feature. The feature-level usage analytic may be a level of the user's ability with the application or an application state that indicates an outcome of a group of users' usage with a particular feature. The feature-level usage analytic provides a developer with insight into the user's behavior when using the application.

Abstract: Resolving conflicting changes to structured data files. A method includes for a structured data file which has both a generic structure and dialects built on top of the generic structure, for which conflicting changes have been made, and where an original version of the structured data, a first version of the structured data and a second version of the structured data exist, determining a dialect of the structured data. The method further includes, based on the determined dialect performing at least one of merge or diff operations on the original version of the structured data, the first version of the structured data and the second version of the structured data.

Abstract: Providing a website map to a user. A method includes gathering information about web pages in a website, including information related to web page relationships, controls, and executable code underlying one or more web pages in the website. A relationship map is created. The relationship map includes representations of relationships between the web pages, the controls and the executable code underlying one or more web pages in the website. The method further includes graphically displaying at least a portion of the relationship map in a graphical user interface at the computing system.

Abstract: Providing a website map to a user. A method includes gathering information about web pages in a website, including information related to web page relationships, controls, and executable code underlying one or more web pages in the website. A relationship map is created. The relationship map includes representations of relationships between the web pages, the controls and the executable code underlying one or more web pages in the website. The method further includes graphically displaying at least a portion of the relationship map in a graphical user interface at the computing system.