Patents by Inventor Alexander Senchenko

Alexander Senchenko 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).

  • Optimized test case selection for quality assurance testing of video games
    Patent number: 11726900
    Abstract: A test case selection system and method uses a test selection model to select test cases from a library of test cases to be used for quality assurance (QA) testing of a software application to maximize the chances of finding bugs from executing the selected test cases. The test case selection model may be a machine learning based regression model trained using outcomes of previous QA testing. In some case, the test case selection system may provide periodic and/or continuous refinement of the test case selection model from one QA testing run to the next. The model refinements may include updating weights associated with the test case selection model in the form of a regression model. Additionally, the test case selection system may provide performance analytics between a test case selection model-based selection of test cases and random selection of test cases.
    Type: Grant
    Filed: July 26, 2021
    Date of Patent: August 15, 2023
    Assignee: Electronic Arts Inc.
    Inventors: Milan Culibrk, Alexander Senchenko, Dan Ispir
  • OPTIMIZED TEST CASE SELECTION FOR QUALITY ASSURANCE TESTING OF VIDEO GAMES
    Publication number: 20210349812
    Abstract: A test case selection system and method uses a test selection model to select test cases from a library of test cases to be used for quality assurance (QA) testing of a software application to maximize the chances of finding bugs from executing the selected test cases. The test case selection model may be a machine learning based regression model trained using outcomes of previous QA testing. In some case, the test case selection system may provide periodic and/or continuous refinement of the test case selection model from one QA testing run to the next. The model refinements may include updating weights associated with the test case selection model in the form of a regression model. Additionally, the test case selection system may provide performance analytics between a test case selection model-based selection of test cases and random selection of test cases.
    Type: Application
    Filed: July 26, 2021
    Publication date: November 11, 2021
    Applicant: Electronic Arts Inc.
    Inventors: Milan Culibrk, Alexander Senchenko, Dan Ispir
  • Optimized test case selection for quality assurance testing of video games
    Patent number: 11074161
    Abstract: A test case selection system and method uses a test selection model to select test cases from a library of test cases to be used for quality assurance (QA) testing of a software application to maximize the chances of finding bugs from executing the selected test cases. The test case selection model may be a machine learning based regression model trained using outcomes of previous QA testing. In some case, the test case selection system may provide periodic and/or continuous refinement of the test case selection model from one QA testing run to the next. The model refinements may include updating weights associated with the test case selection model in the form of a regression model. Additionally, the test case selection system may provide performance analytics between a test case selection model-based selection of test cases and random selection of test cases.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: July 27, 2021
    Assignee: Electronic Arts Inc.
    Inventors: Milan Culibrk, Alexander Senchenko, Dan Ispir
  • OPTIMIZED TEST CASE SELECTION FOR QUALITY ASSURANCE TESTING OF VIDEO GAMES
    Publication number: 20200310948
    Abstract: A test case selection system and method uses a test selection model to select test cases from a library of test cases to be used for quality assurance (QA) testing of a software application to maximize the chances of finding bugs from executing the selected test cases. The test case selection model may be a machine learning based regression model trained using outcomes of previous QA testing. In some case, the test case selection system may provide periodic and/or continuous refinement of the test case selection model from one QA testing run to the next. The model refinements may include updating weights associated with the test case selection model in the form of a regression model. Additionally, the test case selection system may provide performance analytics between a test case selection model-based selection of test cases and random selection of test cases.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Applicant: Electronic Arts, Inc
    Inventors: Milan Culibrk, Alexander Senchenko, Dan Ispir