Patents by Inventor Todd Stadelhofer

Todd Stadelhofer 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).

  • Adaptively generated program model
    Patent number: 11983091
    Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.
    Type: Grant
    Filed: March 25, 2022
    Date of Patent: May 14, 2024
    Assignee: GitLab B.V.
    Inventors: Julian Thome, Isaac Dawson, James Johnson, Zach Rice, Daniel Searles, Lucas Charles, Mark Art, Taylor McCaslin, Thomas Woodham, Todd Stadelhofer
  • ADAPTIVELY GENERATED PROGRAM MODEL
    Publication number: 20230305942
    Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.
    Type: Application
    Filed: March 25, 2022
    Publication date: September 28, 2023
    Inventors: Julian Thome, Isaac Dawson, James Johnson, Zach Rice, Daniel Searles, Lucas Charles, Mark Art, Taylor McCaslin, Thomas Woodham, Todd Stadelhofer