Patents by Inventor Benjamin H Ellis

Benjamin H Ellis 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).

  • Patent number: 11042472
    Abstract: Methods and apparatus are described by which artificial intelligence (AI) is used to enable the rapid development of reliable test suites for web and mobile applications. An AI agent guided by reinforcement learning explores an application-under-test (AUT), interacting with the AUT to traverse the flows through the AUT by seeking novel application states. A subset of these flows is then identified as being representative of the functionality of the AUT. The interactions between the AI agent and the AUT that define these identified flows form the basis for the test suite.
    Type: Grant
    Filed: September 10, 2019
    Date of Patent: June 22, 2021
    Assignee: Sauce Labs Inc.
    Inventors: Fernando Vidal, Benjamin H. Ellis, Bradley Scott Adelberg
  • Publication number: 20210073110
    Abstract: Methods and apparatus are described by which artificial intelligence (AI) is used to enable the rapid development of reliable test suites for web and mobile applications. An AI agent guided by reinforcement learning explores an application-under-test (AUT), interacting with the AUT to traverse the flows through the AUT by seeking novel application states. A subset of these flows is then identified as being representative of the functionality of the AUT. The interactions between the AI agent and the AUT that define these identified flows form the basis for the test suite.
    Type: Application
    Filed: September 10, 2019
    Publication date: March 11, 2021
    Inventors: Fernando Vidal, Benjamin H. Ellis, Bradley Scott Adelberg
  • Patent number: 10942837
    Abstract: Methods and apparatus are described by which time-series data captured during the automated testing of software applications may be analyzed. Change-point detection is used to partition the time-series data, and an expected variance of data within each partition is determined. Because the partitioning of the test data provides a high level of confidence that the data points in a given partition conform to the same distribution, data points that represent meaningful changes in application performance can be more confidently and efficiently identified.
    Type: Grant
    Filed: May 13, 2019
    Date of Patent: March 9, 2021
    Assignee: Sauce Labs Inc.
    Inventors: Fernando Vidal, Benjamin H Ellis
  • Publication number: 20200364133
    Abstract: Methods and apparatus are described by which time-series data captured during the automated testing of software applications may be analyzed. Change-point detection is used to partition the time-series data, and an expected variance of data within each partition is determined. Because the partitioning of the test data provides a high level of confidence that the data points in a given partition conform to the same distribution, data points that represent meaningful changes in application performance can be more confidently and efficiently identified.
    Type: Application
    Filed: May 13, 2019
    Publication date: November 19, 2020
    Inventors: Fernando Vidal, Benjamin H Ellis