Patents by Inventor Bengt Wisen Pederson

Bengt Wisen Pederson 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).

  • Automated machine learning test system
    Patent number: 11775878
    Abstract: A computing device selects new test configurations for testing software. Software under test is executed with first test configurations to generate a test result for each test configuration. Each test configuration includes a value for each test parameter where each test parameter is an input to the software under test. A predictive model is trained using each test configuration of the first test configurations in association with the test result generated for each test configuration based on an objective function value. The predictive model is executed with second test configurations to predict the test result for each test configuration of the second test configurations. Test configurations are selected from the second test configurations based on the predicted test results to define third test configurations. The software under test is executed with the defined third test configurations to generate the test result for each test configuration of the third test configurations.
    Type: Grant
    Filed: November 10, 2021
    Date of Patent: October 3, 2023
    Assignee: SAS Institute Inc.
    Inventors: Yan Gao, Joshua David Griffin, Yu-Min Lin, Bengt Wisen Pederson, Ricky Dee Tharrington, Jr., Pei-Yi Tan, Raymond Eugene Wright
  • AUTOMATED MACHINE LEARNING TEST SYSTEM
    Publication number: 20220198340
    Abstract: A computing device selects new test configurations for testing software. Software under test is executed with first test configurations to generate a test result for each test configuration. Each test configuration includes a value for each test parameter where each test parameter is an input to the software under test. A predictive model is trained using each test configuration of the first test configurations in association with the test result generated for each test configuration based on an objective function value. The predictive model is executed with second test configurations to predict the test result for each test configuration of the second test configurations. Test configurations are selected from the second test configurations based on the predicted test results to define third test configurations. The software under test is executed with the defined third test configurations to generate the test result for each test configuration of the third test configurations.
    Type: Application
    Filed: November 10, 2021
    Publication date: June 23, 2022
    Inventors: Yan Gao, Joshua David Griffin, Yu-Min Lin, Bengt Wisen Pederson, Ricky Dee Tharrington,, JR., Pei-Yi Tan, Raymond Eugene Wright