Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for optimizing performance issues. One of the methods includes maintaining, for a plurality of devices at least some of which have different contexts, metric data for an application that executed on each of the plurality of devices; determining, for a metric attribute from a plurality of metric attributes and a subset of the plurality of devices each of which have at least one common context, a potential performance issue for the subset of the plurality of devices using aggregated metric data for the metric attribute; determining, using at least a portion of the aggregated metric data, a portion of a code base or a hardware subcomponent that likely caused the potential performance issue; and providing data for the portion of the code base or the hardware subcomponent that likely caused the potential performance issue.

Abstract: In an example method, a system receives diagnostic data from a plurality of electronic devices, the diagnostic data representing resource usage by applications on the plurality of electronic devices, application names associated with the applications, application version identifiers associated with the applications, and call-stacks associated with the resource usage by the applications. The system categorizes the resource usage based on the application names, the application version identifiers, and the call-stacks, including determining signatures based on the call-stacks, and categorizing the resource usage based on the signatures, the application names, and the application version identifiers. Further, the system generates a data set representing the categorization of the resource usage.

Abstract: A server computer may receive diagnostic logs from a plurality of electronic devices, each having a particular application installed. The diagnostic logs include information about call stacks within the particular application on the plurality of electronic devices for writing data to a storage device that is on each of the plurality of electronic devices. The server computer may filter out a set of call-paths from the call stacks to obtain a set of functions that can be used identify a set of call-path signatures. The server computer may for each function, determine a cumulative measure of write operations to the storage device performed by the function across the electronic devices and identify at least one function from the set of call-path signatures matching one or more predetermined criteria associated with the cumulative measures. The server computer may provide a notification and a corrective action to a developer.

Abstract: A server computer may receive diagnostic logs from a plurality of electronic devices, each having a particular application installed. The diagnostic logs include information about call stacks within the particular application on the plurality of electronic devices for writing data to a storage device that is on each of the plurality of electronic devices. The server computer may filter out a set of call-paths from the call stacks to obtain a set of functions that can be used identify a set of call-path signatures. The server computer may for each function, determine a cumulative measure of write operations to the storage device performed by the function across the electronic devices and identify at least one function from the set of call-path signatures matching one or more predetermined criteria associated with the cumulative measures. The server computer may provide a notification and a corrective action to a developer.

Abstract: Embodiments of the present disclosure present devices, methods, and computer readable medium for techniques for measuring operational performance metrics, and presenting these metrics through an application programming interface (API) for developers to access for optimizing their applications. Exemplary metrics can include central processing unit or graphics processing unit time, foreground/background time, networking bytes (per application), location activity, display average picture luminance, cellular networking condition, peak memory, number of logical writes, launch and resume time, frame rates, and hang time. Regional markers can also be used to measure specific metrics for in application tasks. The techniques provide multiple user interfaces to help developers recognize the important metrics to optimize the performance of their applications. The data can be normalized over various different devices having different battery size, screen size, and processing requirements.

Abstract: Embodiments of the present disclosure present devices, methods, and computer readable medium for techniques for measuring operational performance metrics, and presenting these metrics through an application programming interface (API) for developers to access for optimizing their applications. Exemplary metrics can include central processing unit or graphics processing unit time, foreground/background time, networking bytes (per application), location activity, display average picture luminance, cellular networking condition, peak memory, number of logical writes, launch and resume time, frame rates, and hang time. Regional markers can also be used to measure specific metrics for in application tasks. The techniques provide multiple user interfaces to help developers recognize the important metrics to optimize the performance of their applications. The data can be normalized over various different devices having different battery size, screen size, and processing requirements.

Abstract: Embodiments of the present disclosure present devices, methods, and computer readable medium for techniques for measuring operational performance metrics, and presenting these metrics through an application programming interface (API) for developers to access for optimizing their applications. Exemplary metrics can include central processing unit or graphics processing unit time, foreground/background time, networking bytes (per application), location activity, display average picture luminance, cellular networking condition, peak memory, number of logical writes, launch and resume time, frame rates, and hang time. Regional markers can also be used to measure specific metrics for in application tasks. The techniques provide multiple user interfaces to help developers recognize the important metrics to optimize the performance of their applications. The data can be normalized over various different devices having different battery size, screen size, and processing requirements.

Abstract: Examples are disclosed herein that relate to estimating and predicting vehicular fuel use. One example estimates fuel usage by a vehicle during a trip by obtaining sensor measurements from one or more sensors of a mobile computing device during the trip, determining a plurality of trip features from the sensor measurements, each trip feature representing an aspect of one or more of energy produced and energy consumed during the trip, obtaining vehicle-specific parameters of the vehicle, and determining an estimated fuel usage from the vehicle-specific parameters and the plurality of trip features for output by the computing device.

Abstract: A method, system and program product comprise receiving spectrum data from one or more WiFi communication devices being configured to be operable as observers of transmissions within a frequency band associated with a WiFi communication system. The spectrum data at least comprises signal levels and timing information for WiFi communication signals and non-WiFi signals observed within the frequency band. WiFi interferers are distinguished using at least the signal levels and timing information for the non-WiFi signals. A real-time interference impact on the observed WiFi communication signals for each of the distinguished WIFi interferers is determined.

Abstract: A method, system and program product comprise generating spectral samples from at least one radio communication device being configured to be operable as an observer of transmissions within a frequency band divided into one or more sub-bands associated with communications of the radio communication device. The spectral samples at least comprise signal levels and timing information for observed signals within the sub-bands. Spectral samples determined to be decodable communications are purged. Pulses in the spectral samples are identified. The identified pulses at least comprise a power, a center frequency and a bandwidth. A list of identified pulses for the sub-bands is maintained. At least a set of features of the identified pulses in the list is extracted. A presence of at least one radio frequency device associated with the set is detected.

Abstract: A method, system and program product comprise receiving spectrum data from one or more WiFi communication devices being configured to be operable as observers of transmissions within a frequency band associated with a WiFi communication system. The spectrum data at least comprises signal levels and timing information for WiFi communication signals and non-WiFi signals observed within the frequency band. WiFi interferers are distinguished using at least the signal levels and timing information for the non-WiFi signals. A real-time interference impact on the observed WiFi communication signals for each of the distinguished WIFi interferers is determined.