Patents by Inventor Eynan Drori

Eynan Drori has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • System and method for troubleshooting abnormal behavior of an application
    Patent number: 11526422
    Abstract: A method for troubleshooting abnormal behavior of an application hosted on a networked computer system. The method may be implemented by a root cause analyzer. The method includes tracking a single application performance metric across all the clients of an application hosted on a networked computer system and analyzing an aggregated application based on the single application metric. The method involves determining outlier client attributes associated with an abnormal transaction of the application and ranking the outlier client attributes based on comparisons of historical and current abnormal transactions. The method associates one or more of the ranked outlier client attributes with the root cause of the current abnormal transaction. Association rule learning is used to associate one or more of the ranked outlier client attributes with the root cause.
    Type: Grant
    Filed: December 30, 2019
    Date of Patent: December 13, 2022
    Assignee: BMC Software, Inc.
    Inventors: Eynan Drori, Sudhir Sangra
  • SYSTEM AND METHOD FOR TROUBLESHOOTING ABNORMAL BEHAVIOR OF AN APPLICATION
    Publication number: 20210149789
    Abstract: A method for troubleshooting abnormal behavior of an application hosted on a networked computer system. The method may be implemented by a root cause analyzer. The method includes tracking a single application performance metric across all the clients of an application hosted on a networked computer system and analyzing an aggregated application based on the single application metric. The method involves determining outlier client attributes associated with an abnormal transaction of the application and ranking the outlier client attributes based on comparisons of historical and current abnormal transactions. The method associates one or more of the ranked outlier client attributes with the root cause of the current abnormal transaction. Association rule learning is used to associate one or more of the ranked outlier client attributes with the root cause.
    Type: Application
    Filed: December 30, 2019
    Publication date: May 20, 2021
    Inventors: Eynan Drori, Sudhir Sangra