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    TECHNIQUES AND DEVICES FOR QUALITATIVE DISK WRITES PERFORMANCE ANTI-PATTERN DETECTION AND MITIGATION
    2.
    发明申请
    TECHNIQUES AND DEVICES FOR QUALITATIVE DISK WRITES PERFORMANCE ANTI-PATTERN DETECTION AND MITIGATION 有权

    公开(公告)号：US20220392486A1

    公开(公告)日：2022-12-08

    申请号：US17500746

    申请日：2021-10-13

    Applicant: APPLE INC.

    Inventor： Sheyas Binnamangala Prabhu ,  Anshul Dawra ,  Kaiehu H. Kaahaaina ,  Ashish Patro ,  Akhil Bhutani ,  Komlan J. Attiogbe ,  Shefali Saboo ,  Phillip Azar

    IPC: G11B5/012

    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.

    LOGGING TECHNIQUES FOR THIRD PARTY APPLICATION DATA
    4.
    发明申请
    LOGGING TECHNIQUES FOR THIRD PARTY APPLICATION DATA 审中-公开

    公开(公告)号：US20200379878A1

    公开(公告)日：2020-12-03

    申请号：US16671093

    申请日：2019-10-31

    Applicant: Apple Inc.

    Inventor： Amit K. Vyas ,  Abhinav Pathak ,  Anthony R. Newnam ,  Phillip J. Azar ,  Ashish Patro ,  Prajakta S. Karandikar ,  Daniel J. Etter ,  Conor J. O'Reilly ,  Andreas C. Bergen ,  Nehal Bhandari ,  Jeffrey S. Lale ,  Andrew P. Sakai ,  Terrence R. Long ,  Soren C. Spies

    IPC: G06F11/36

    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. The user interfaces can provide an intelligent method for visualizing performance changes for significant changes in application versions.

    SYSTEMS AND TECHNIQUES FOR ANALYZING RESOURCE USAGE BY APPLICATIONS OF AN ELECTRONIC DEVICE
    5.
    发明申请
    SYSTEMS AND TECHNIQUES FOR ANALYZING RESOURCE USAGE BY APPLICATIONS OF AN ELECTRONIC DEVICE 有权

    公开(公告)号：US20240427681A1

    公开(公告)日：2024-12-26

    申请号：US18404714

    申请日：2024-01-04

    Applicant: Apple Inc.

    Inventor： Akhil Bhutani ,  Anshul Dawra ,  Shreyas Binnamangala Prabhu ,  Phillip J. Azar ,  Ashish Patro ,  Alex W. Fu

    IPC: G06F11/30 ,  G06F16/2458 ,  G06F16/28

    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.

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