Patents by Inventor Neelakantan Sundaresan

Neelakantan Sundaresan 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).

  • Dynamic experimentation evaluation system
    Patent number: 11526421
    Abstract: A dynamic experimentation evaluation system provides a framework in which a continuous stream of metric data is monitored to establish a causal relationship between changes in a software program and the effect of user-observable behavior. In one aspect, an A/B test is performed continuously on a stream of metric data representing the usage of a control version of software product and the usage of a treatment version of the software product. A sequential probability ratio test (SPRT) is used as the test statistic to determine when to terminate the test and produce results within a specific confidence interval and controlled error rate.
    Type: Grant
    Filed: September 14, 2018
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Neelakantan Sundaresan, Cenzhuo Yao
  • Automated program repair tool
    Patent number: 11526424
    Abstract: An automated program repair tool utilizes a neural transformer model with attention to predict the contents of a bug repair in the context of source code having a bug of an identified bug type. The neural transformer model is trained on a large unsupervised corpus of source code using a span-masking denoising optimization objective, and fine-tuned on a large supervised dataset of triplets containing a bug-type annotation, software bug, and repair. The bug-type annotation is derived from an interprocedural static code analyzer. A bug type edit centroid is computed for each bug type and used in the inference decoding phase to generate the bug repair.
    Type: Grant
    Filed: June 10, 2020
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING LLC.
    Inventors: Shao Kun Deng, Neelakantan Sundaresan, Alexey Svyatkovskiy, Michele Tufano
  • Cloud resource management using machine learning
    Patent number: 11526370
    Abstract: A cloud resource management system trains, through ensemble learning, multiple time series forecasting models to forecast a future idle time of a virtual machine operating on a cloud computing service. The models are trained on historical usage and metric data of the virtual machine. The metric data includes CPU usage, disk usage and network usage. A select one of the models having the best accuracy for a target virtual machine is used in a production run to predict when the virtual machine will be idle. At this time, the virtual machine may be automatically shutdown in order to reduce the expense associated with the continued operation of the virtual machine.
    Type: Grant
    Filed: March 10, 2019
    Date of Patent: December 13, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Yiping Dou, Tanmayee Prakash Kamath, Arun Ramanathan Chandrasekhar, Claude Remillard, Mark Steven Schnitzer, Balan Subramanian, Neelakantan Sundaresan, Yijin Wei
  • Transfer learning system for automated software engineering tasks
    Patent number: 11521075
    Abstract: A transfer learning system is used for the development of neural transformer models pertaining to software engineering tasks. The transfer learning system trains source code domain neural transformer models with attention in various configurations on a large corpus of unsupervised training dataset of source code programs and/or source code-related natural language text. A web service provides the trained models for use in developing a model that may be fine-tuned on a supervised training dataset associated with a software engineering task thereby generating a tool to perform the software engineering task.
    Type: Grant
    Filed: June 30, 2020
    Date of Patent: December 6, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Colin Bruce Clement, Dawn Drain, Neelakantan Sundaresan, Alexey Svyatkovskiy
  • Multi-lingual code generation with zero-shot inference
    Patent number: 11513774
    Abstract: A neural transformer model with attention is trained to predict candidates to complete a line of source code with a zero-inference capability. The model is trained on an unsupervised training dataset that includes features from source code written in multiple programming languages. The features include a file-level context and a local context, where the file-level context includes a global context, a class context, a function context, and/or a method context for each class, function and/or method of the source code programs used in the training dataset. The local context includes method bodies, function bodies, and/or stand-alone code of main method routines. From these features, the model is able to learn to predict an ordered sequence of code elements that complete a line of source code in a programming language seen and not seen during training.
    Type: Grant
    Filed: January 3, 2021
    Date of Patent: November 29, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Colin Bruce Clement, Shuai Lu, Neelakantan Sundaresan, Alexey Svyatkovskiy, Duyu Tang
  • CODE COMPLETION WITH HOLES
    Publication number: 20220374208
    Abstract: A code completion tool uses a neural transformer model with attention to generate syntactically-correct candidates with holes to complete a partially-formed code snippet. The model is trained to predict the expansion of non-terminal symbols of the production rules of the underlying grammar of the code snippet without being constrained to a left-to-right expansion order. A hole is a non-terminal symbol of the grammar of a programming language that marks a position in a candidate where the code completion engine is not certain of the production rule that should be used to expand the non-terminal symbol. The hole allows the code completion engine to expand other non-terminal symbols in a candidate and allow the user to guide the expansion of the holes in a candidate.
    Type: Application
    Filed: May 15, 2021
    Publication date: November 24, 2022
    Inventors: MILTIADIS ALLAMANIS, DAYA GUO, SHAO KUN DENG, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY
  • Searchable texture index
    Patent number: 11494823
    Abstract: Electronic content that has a tactile dimension when presented on a tactile-enabled computing device may be referred to as tactile-enabled content. A tactile-enabled device is a device that is capable of presenting tactile-enabled content in a manner that permits a user to experience tactile quality of electronic content. In one example embodiment, a system is provided for generating content that has a tactile dimension when presented on a tactile-enabled device.
    Type: Grant
    Filed: January 21, 2021
    Date of Patent: November 8, 2022
    Assignee: eBay Inc.
    Inventors: Neelakantan Sundaresan, Anurag Bhardwaj, Robinson Piramuthu
  • DETECTION OF RUNTIME ERRORS USING MACHINE LEARNING
    Publication number: 20220342800
    Abstract: Runtime errors in a source code program are detected in advance of execution by machine learning models. Features representing a context of a runtime error are extracted from source code programs to train a machine learning model, such as a random forest classifier, to predict the likelihood that a code snippet has a particular type of runtime error. The features are extracted from a syntax-type tree representation of each method in a program. A model is generated for distinct runtime errors, such as arithmetic overflow, and conditionally uninitialized variables.
    Type: Application
    Filed: July 4, 2022
    Publication date: October 27, 2022
    Inventors: SHAUN MILLER, KALPATHY SITARAMAN SIVARAMAN, NEELAKANTAN SUNDARESAN, YIJIN WEI, ROSHANAK ZILOUCHIAN MOGHADDAM
  • Recommendations based on branding
    Patent number: 11475501
    Abstract: A method and a system for providing recommendations based on branding are disclosed. In example embodiments, an index comprising predetermined brand relationships is maintained. Each predetermined brand relationship comprises a first brand, a second brand, and a recommendation score between the first brand and the second brand. A corpus containing a plurality of user queries is also maintained. A seed set of brands corresponding to a category in the index is expanded by accessing the corpus containing the plurality of user queries, evaluating user queries of the plurality of user queries that contain a disjunction of brand terms, and identifying a new brand to add to the seed set based on the evaluating.
    Type: Grant
    Filed: August 13, 2019
    Date of Patent: October 18, 2022
    Assignee: PayPal, Inc.
    Inventors: Nishith Parikh, Neelakantan Sundaresan
  • FREQUENT SOURCE CODE PATTERN MINING
    Publication number: 20220326918
    Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.
    Type: Application
    Filed: June 28, 2022
    Publication date: October 13, 2022
    Inventors: CHRISTIAN ALMA BIRD, SHENGYU FU, NEELAKANTAN SUNDARESAN, NINA WANG, SHUO ZHANG
  • SEMI-SUPERVISED TRANSLATION OF SOURCE CODE PROGRAMS USING NEURAL TRANSFORMERS
    Publication number: 20220308848
    Abstract: An automated system for translating source code written in one programming language into a different programming language utilizes a neural transformer with attention trained on semi-supervised data. The model is jointly pre-trained with a masked language model objective and an autoregressive objective on a large unsupervised source code corpus to learn to comprehend the syntactic structure and semantics of source code. The pre-trained model is then fine-tuned with a token-type prediction objective and an autoregressive objective on supervised translation tasks and data augmented tasks to learn to translate source code from one programming language into a different programming language.
    Type: Application
    Filed: March 25, 2021
    Publication date: September 29, 2022
    Inventors: COLIN BRUCE CLEMENT, DAWN DRAIN, NEELAKANTAN SUNDARESAN, ALEXEY SVYATKOVSKIY, CHEN WU
  • Community based network shopping
    Patent number: 11455677
    Abstract: A system receives item data corresponding to an item list from a user. The item list may include one or more items. The system communicates the item list to a community group associated with the user and the system then receives member data from one or more members of the community group, wherein the member data is associated with the one or more items on the item list.
    Type: Grant
    Filed: October 16, 2020
    Date of Patent: September 27, 2022
    Assignee: eBay Inc.
    Inventor: Neelakantan Sundaresan
  • Systems and methods for saving and presenting a state of a communication session
    Patent number: 11455348
    Abstract: A system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for saving and presenting a state of a communication session are presented. The communication session may be established between a client device and an application server of a content publisher, and may include the presentation of content on the client device. In some embodiments, the method may include receiving user input to save a state of the communication session, and in response, temporarily storing session data representative of the state of the communication session for a predetermined duration of the communication session. The method may further include generating and presenting an interface that includes a visual representation of the session data, and allows a user to return to the saved state of the communication session.
    Type: Grant
    Filed: February 17, 2020
    Date of Patent: September 27, 2022
    Assignee: eBay Inc.
    Inventors: Esmeralda Carrillo, Kristy Brambila, Cassandra Gordon, Enrica Montilla Beltran, Neelakantan Sundaresan
  • Social sharing system
    Patent number: 11444991
    Abstract: A system, computer-readable storage medium storing at least one program, and computer-implemented method for providing recommendations based on social network sharing activity. Sharing activity relating to the sharing of the content item on a social network by a first user is accessed. Consumption information related to the consumption of the content item. A correlation between the sharing activity and the consumption information is determined. A recommendation is then generated based on the correlation.
    Type: Grant
    Filed: August 3, 2020
    Date of Patent: September 13, 2022
    Assignee: PayPal, Inc.
    Inventors: Neelakantan Sundaresan, Atish Das Sarma, Si Si, Elizabeth Churchill
  • Command-line script generation with relevance search
    Patent number: 11436236
    Abstract: A term-weighting and document-scoring function is used to search for a command line interface (CLI) script that is likely relevant to an operation specified in a natural language query. CLI scripts are created to perform various operations of a CLI-based application. A CLI script is associated with a description document having keywords associated with the individual commands used in the CLI script. The relevance of a CLI script to an intended operation is based on the term-weighting and document-scoring function which is applied to each component of each command in a CLI script and weighted accordingly.
    Type: Grant
    Filed: May 1, 2020
    Date of Patent: September 6, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
    Inventors: Spandan Garg, Yevhen Mohylevskyy, Jason R. Shaver, Neelakantan Sundaresan, Roshanak Zilouchian Moghaddam
  • NEURAL COMMAND LINE INTERFACE EXAMPLE GENERATION
    Publication number: 20220253712
    Abstract: An example generator tool generates an example illustrating correct usage of a command of a command line interface. A command may include a command name, zero or more subcommands, and one or more parameters with a corresponding parameter value. A template containing the correct syntax of the command is obtained from a template database. Parameter values for the template are generated from a neural transformer with attention given the command template.
    Type: Application
    Filed: April 19, 2021
    Publication date: August 11, 2022
    Inventors: COLIN BRUCE CLEMENT, ROSHANAK ZILOUCHIAN MOGHADDAM, NEELAKANTAN SUNDARESAN
  • SOURCE CODE GENERATION USING CODE TEMPLATES WITH NEURAL TRANSFORMERS
    Publication number: 20220244952
    Abstract: A source code generation system uses a neural transformer model with attention to predict candidate method bodies given a method docstring, method signature, and one or more method templates. The method templates are derived from intent-snippet pairs from StackOverflow question/answer pairs or template methods from GitHub. Joint embeddings are generated for the method bodies of the method templates and associated method docstrings for quick retrieval. A code completion system uses the source code generation system to generate candidate method bodies to complete a method signature and/or method docstring using the method templates.
    Type: Application
    Filed: April 1, 2021
    Publication date: August 4, 2022
    Inventors: MIKHAIL BRESLAV, COLIN BRUCE CLEMENT, DAWN DRAIN, CHANGRAN HU, NEELAKANTAN SUNDARESAN, CHEN WU
  • AUTOMATED PROGRAM REPAIR USING STACK TRACES AND BACK TRANSLATIONS
    Publication number: 20220245056
    Abstract: An automated program repair system uses a neural transformer model with attention to predict a bug-free version of a method having a source code bug identified in an associated stack trace. The neural transformer model is pre-trained with English language text and the source code of a target programming language. The pre-trained neural transformer model is trained to create synthetic bugs in bug-free methods. The bug-free methods with the synthetic bugs are executed with a test case to obtain a stack trace of the source code bug. The method with the synthetic bug, without the bug, and its stack trace are used to train the neural transformer model to predict repairs for buggy methods.
    Type: Application
    Filed: March 25, 2021
    Publication date: August 4, 2022
    Inventors: COLIN BRUCE CLEMENT, DAWN DRAIN, GUILLERMO SERRATO CASTILLA, NEELAKANTAN SUNDARESAN
  • Detection of runtime errors using machine learning
    Patent number: 11403207
    Abstract: Runtime errors in a source code program are detected in advance of execution by machine learning models. Features representing a context of a runtime error are extracted from source code programs to train a machine learning model, such as a random forest classifier, to predict the likelihood that a code snippet has a particular type of runtime error. The features are extracted from a syntax-type tree representation of each method in a program. A model is generated for distinct runtime errors, such as arithmetic overflow, and conditionally uninitialized variables.
    Type: Grant
    Filed: February 28, 2020
    Date of Patent: August 2, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Shaun Miller, Kalpathy Sitaraman Sivaraman, Neelakantan Sundaresan, Yijin Wei, Roshanak Zilouchian Moghaddam
  • Frequent source code pattern mining
    Patent number: 11392354
    Abstract: A data mining technique is used to find large frequently-occurring source code patterns from methods/APIs that can be used in code development. Simplified trees that represent the syntactic structure and type and method usage of a source code fragment, such as a method, are mined to find closed and maximal frequent subtrees which represent the largest frequently-occurring source code patterns or idioms associated with a particular type and method usage. These idioms are then used in an idiom web service and/or a code completion system to assist users in the development of source code programs.
    Type: Grant
    Filed: March 31, 2020
    Date of Patent: July 19, 2022
    Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.
    Inventors: Christian Alma Bird, Shengyu Fu, Neelakantan Sundaresan, Nina Wang, Shuo Zhang