Patents by Inventor Luca Buratti

Luca Buratti 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).

  • Contextual embeddings for improving static analyzer output
    Patent number: 11765193
    Abstract: In a computer-implemented method for improving a static analyzer output, a processor receives a labeled data set with labeled true vulnerabilities and labeled false vulnerabilities. A processor receives pretrained contextual embeddings from a contextual embeddings model. A processor maps the true vulnerabilities and the false vulnerabilities to the pretrained contextual embeddings model. A processor generates a fine-tuned model with classifications for true vulnerabilities.
    Type: Grant
    Filed: December 30, 2020
    Date of Patent: September 19, 2023
    Assignee: International Business Machines Corporation
    Inventors: Saurabh Pujar, Luca Buratti, Alessandro Morari, Jim Alain Laredo, Mihaela Ancuta Bornea, Jeffrey Scott McCarley, Yunhui Zheng
  • Building pre-trained contextual embeddings for programming languages using specialized vocabulary
    Patent number: 11429352
    Abstract: A method, a computer system, and a computer program product for building pre-trained contextual embeddings is provided. Embodiments of the present invention may include collecting programming code. Embodiments of the present invention may include loading and preparing the programming code using a specialized programming language keywords-based vocabulary. Embodiments of the present invention may include creating contextual embeddings for the programming code. Embodiments of the present invention may include storing the contextual embeddings.
    Type: Grant
    Filed: July 1, 2020
    Date of Patent: August 30, 2022
    Assignee: International Business Machines Corporation
    Inventors: Saurabh Pujar, Luca Buratti, Alessandro Morari, Jim Alain Laredo, Alfio Massimiliano Gliozzo, Gaetano Rossiello
  • CONTEXTUAL EMBEDDINGS FOR IMPROVING STATIC ANALYZER OUTPUT
    Publication number: 20220210178
    Abstract: In a computer-implemented method for improving a static analyzer output, a processor receives a labeled data set with labeled true vulnerabilities and labeled false vulnerabilities. A processor receives pretrained contextual embeddings from a contextual embeddings model. A processor maps the true vulnerabilities and the false vulnerabilities to the pretrained contextual embeddings model. A processor generates a fine-tuned model with classifications for true vulnerabilities.
    Type: Application
    Filed: December 30, 2020
    Publication date: June 30, 2022
    Inventors: Saurabh Pujar, Luca Buratti, Alessandro Morari, Jim Alain Laredo, Mihaela Ancuta Bornea, Jeffrey Scott McCarley, Yunhui Zheng
  • BUILDING PRE-TRAINED CONTEXTUAL EMBEDDINGS FOR PROGRAMMING LANGUAGES USING SPECIALIZED VOCABULARY
    Publication number: 20220004365
    Abstract: A method, a computer system, and a computer program product for building pre-trained contextual embeddings is provided. Embodiments of the present invention may include collecting programming code. Embodiments of the present invention may include loading and preparing the programming code using a specialized programming language keywords-based vocabulary. Embodiments of the present invention may include creating contextual embeddings for the programming code. Embodiments of the present invention may include storing the contextual embeddings.
    Type: Application
    Filed: July 1, 2020
    Publication date: January 6, 2022
    Inventors: Saurabh Pujar, Luca Buratti, Alessandro Morari, Jim Alain Laredo, Alfio Massimiliano Gliozzo, Gaetano Rossiello
  • VULNERABILITY ANALYSIS USING CONTEXTUAL EMBEDDINGS
    Publication number: 20220004642
    Abstract: A method, a computer system, and a computer program product for vulnerability analysis using contextual embeddings is provided. Embodiments of the present invention may include collecting labeled code snippets. Embodiments of the present invention may include preparing the labeled code snippets. Embodiments of the present invention may include tokenizing the labeled code snippets. Embodiments of the present invention may include fine-tuning a model. Embodiments of the present invention may include collecting unlabeled code snippets. Embodiments of the present invention may include predicting a vulnerability of the unlabeled code snippets using the model.
    Type: Application
    Filed: July 1, 2020
    Publication date: January 6, 2022
    Inventors: Saurabh Pujar, Luca Buratti, Alessandro Morari, Jim Alain Laredo, Alfio Massimiliano Gliozzo, Gaetano Rossiello