Patents by Inventor Christian Bird

Christian Bird 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).

  • Publication number: 20250036911
    Abstract: An automated system for resolving program merges uses neural transformers with attention. In one aspect, a neural encoder transformer model is trained from developer-resolved merge conflicts to learn to predict a resolution strategy that aids a developer in constructing a merged program. In a second aspect, a neural decoder transformer model is trained on the syntax and semantics of different source code programming languages to predict a merge resolution consisting of interleaved lines of source code from programs A, B, or O, where programs A and B contain changes to code base O.
    Type: Application
    Filed: October 11, 2024
    Publication date: January 30, 2025
    Inventors: CHRISTIAN BIRD, SHUVENDU K. LAHIRI, TODD DOUGLAS MYTKOWICZ, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Patent number: 12159211
    Abstract: An automated system for resolving program merges uses neural transformers with attention. In one aspect, a neural encoder transformer model is trained from developer-resolved merge conflicts to learn to predict a resolution strategy that aids a developer in constructing a merged program. In a second aspect, a neural decoder transformer model is trained on the syntax and semantics of different source code programming languages to predict a merge resolution consisting of interleaved lines of source code from programs A, B, or O, where programs A and B contain changes to code base O.
    Type: Grant
    Filed: February 12, 2021
    Date of Patent: December 3, 2024
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Christian Bird, Shuvendu K. Lahiri, Todd Douglas Mytkowicz, Neelakantan Sundaresan, Alexey Svyatkovskiy
  • Publication number: 20220164626
    Abstract: An automated system for resolving program merges uses neural transformers with attention. In one aspect, a neural encoder transformer model is trained from developer-resolved merge conflicts to learn to predict a resolution strategy that aids a developer in constructing a merged program. In a second aspect, a neural decoder transformer model is trained on the syntax and semantics of different source code programming languages to predict a merge resolution consisting of interleaved lines of source code from programs A, B, or O, where programs A and B contain changes to code base O.
    Type: Application
    Filed: February 12, 2021
    Publication date: May 26, 2022
    Inventors: CHRISTIAN BIRD, SHUVENDU K. LAHIRI, TODD DOUGLAS MYTKOWICZ, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Publication number: 20220164672
    Abstract: An automated system for resolving program merges uses a sequence-to-sequence supervised machine learning model trained from developer-resolved merge conflicts to learn to predict a merge resolution to resolve a three-way program merge. The model utilizes an embedding of the merge tuple (A, B, O) which represents the program syntax, program semantics and the intent of the program inputs. The model uses a pointer mechanism to construct the resolved program in terms of the lines of source code found in the input programs.
    Type: Application
    Filed: February 12, 2021
    Publication date: May 26, 2022
    Inventors: CHRISTIAN BIRD, ELIZABETH DINELLA, SHUVENDU K. LAHIRI, TODD DOUGLAS MYTKOWICZ, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Patent number: 9542176
    Abstract: Systems and methods for predicting a software build error are described herein. In one example, a method includes detecting a plurality of changes in software. The method also includes identifying a plurality of change lists, wherein a change list is identified for each of the plurality of changes in the software. Additionally, the method includes identifying a characteristic for each change list in the plurality of change lists. Furthermore, the method includes calculating a plurality of probabilities based at least in part on the characteristic of each of the plurality of change lists, wherein each of the probabilities indicates the likelihood of one of the plurality of change lists creating the software build error. The method also includes reporting the plurality of probabilities of the software build error.
    Type: Grant
    Filed: August 20, 2012
    Date of Patent: January 10, 2017
    Assignee: Microsoft Technology Licensing, LLC
    Inventors: Christian Bird, Thomas Zimmermann
  • Publication number: 20140053135
    Abstract: Systems and methods for predicting a software build error are described herein. In one example, a method includes detecting a plurality of changes in software. The method also includes identifying a plurality of change lists, wherein a change list is identified for each of the plurality of changes in the software. Additionally, the method includes identifying a characteristic for each change list in the plurality of change lists. Furthermore, the method includes calculating a plurality of probabilities based at least in part on the characteristic of each of the plurality of change lists, wherein each of the probabilities indicates the likelihood of one of the plurality of change lists creating the software build error. The method also includes reporting the plurality of probabilities of the software build error.
    Type: Application
    Filed: August 20, 2012
    Publication date: February 20, 2014
    Applicant: Microsoft Corporation
    Inventors: Christian Bird, Thomas Zimmermann
  • Patent number: D713215
    Type: Grant
    Filed: August 13, 2013
    Date of Patent: September 16, 2014
    Assignee: Edge of Belgravia Limited
    Inventor: Christian Bird