Patents by Inventor Nachiappan Nagappan
Nachiappan Nagappan 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).
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Patent number: 11875233Abstract: Systems and methods for automatic recognition of entities related to cloud incidents are described. A method, implemented by at least one processor, for processing cloud incidents related information, including entity names and entity values associated with incidents having a potential to adversely impact products or services offered by a cloud service provider is provided. The method may include using at least one processor, processing the cloud incidents related information to convert at least words and symbols corresponding to a cloud incident into machine learning formatted data. The method may further include using a machine learning pipeline, processing at least a subset of the machine learning formatted data to recognize entity names and entity values associated with the cloud incident.Type: GrantFiled: July 10, 2020Date of Patent: January 16, 2024Assignee: Microsoft Technology Licensing, LLCInventors: Manish Shetty Molahalli, Chetan Bansal, Sumit Kumar, Nikitha Rao, Nachiappan Nagappan, Thomas Michael Josef Zimmermann
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Patent number: 11822518Abstract: A heuristics-based concurrent edit detector (“ConE”) can notify collaborators about potential conflicts that may be caused by edits made by other collaborators. ConE may compare concurrent edits submitted by collaborators, calculate the extent of overlap between two sets of edits, apply one or more filters to balance recall versus precision, and decide whether to alert the collaborators about candidate potential conflicts. ConE may be light-weight and easily scalable to work in a very large environment with numerous collaborators.Type: GrantFiled: November 16, 2022Date of Patent: November 21, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Chandra Sekhar Maddila, Nachiappan Nagappan, Christian Alma Bird
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Publication number: 20230076610Abstract: A heuristics-based concurrent edit detector (“ConE”) can notify collaborators about potential conflicts that may be caused by edits made by other collaborators. ConE may compare concurrent edits submitted by collaborators, calculate the extent of overlap between two sets of edits, apply one or more filters to balance recall versus precision, and decide whether to alert the collaborators about candidate potential conflicts. ConE may be light-weight and easily scalable to work in a very large environment with numerous collaborators.Type: ApplicationFiled: November 16, 2022Publication date: March 9, 2023Applicant: Microsoft Technology Licensing, LLCInventors: Chandra Sekhar Maddila, Nachiappan Nagappan, Christian Alma Bird
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Patent number: 11599814Abstract: A computer implemented method includes receiving an exception generated based on programming code, generating exception features from the received exception, the generated exception features being generated based on a set exception features derived from search logs, and executing a machine learning model on the received exception and generated exception features to provide information from the search logs identified as most helpful to resolve the received exception, wherein the machine learning model was trained on training data comprising extracted exceptions and the set of exception features derived from the search logs.Type: GrantFiled: October 21, 2019Date of Patent: March 7, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Foyzul Hassan, Chetan Bansal, Thomas Michael Josef Zimmermann, Nachiappan Nagappan, Ahmed Awadallah
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Patent number: 11550758Abstract: A heuristics-based concurrent edit detector (“ConE”) can notify collaborators about potential conflicts that may be caused by edits made by other collaborators. ConE may compare concurrent edits submitted by collaborators, calculate the extent of overlap between two sets of edits, apply one or more filters to balance recall versus precision, and decide whether to alert the collaborators about candidate potential conflicts. ConE may be light-weight and easily scalable to work in a very large environment with numerous collaborators.Type: GrantFiled: August 5, 2020Date of Patent: January 10, 2023Assignee: Microsoft Technology Licensing, LLCInventors: Chandra Sekhar Maddila, Nachiappan Nagappan, Christian Alma Bird
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Patent number: 11513773Abstract: A synthesis procedure learns program transformations for a text document, on-the-fly during an edit session, from examples of concrete edits made during the edit session and from an unsupervised set of additional inputs. The additional inputs are derived from explicit feedback from the user and inferred feedback from the user's behavior during the edit session. A reward score, based on anti-unification and provenance analysis, is used to classify the additional inputs as either a positive input or a negative input. Outputs are generated for the positive inputs that are consistent with the existing examples and then used to synthesize a new program transformation. The program transformations are then used to generate code edit suggestions during the edit session.Type: GrantFiled: September 30, 2020Date of Patent: November 29, 2022Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC.Inventors: Shraddha Govind Barke, Xiang Gao, Sumit Gulwani, Alan Thomas Leung, Nachiappan Nagappan, Arjun Radhakrishna, Gustavo Araujo Soares, Ashish Tiwari, Mark Alistair Wilson-Thomas
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Patent number: 11379227Abstract: Embodiments promote searcher productivity and efficient search engine usage by using extraquery context to detect a searcher's intent, and using detected intent to match searches to well-suited search providers. Extraquery context may include cursor location, open files, and other editing information, tool state, tool configuration or environment, project metadata, and other information external to actual search query text. Search intent may be code (seeking snippets) or non-code (seeking documentation), and sub-intents may be distinguished for different kinds of documentation or different programming languages. Search provider capabilities may reflect input formats such as natural language or logical operator usage, or content scope such as web-wide or local, or other search provider technical characteristics.Type: GrantFiled: October 3, 2020Date of Patent: July 5, 2022Assignee: Microsoft Technology Licensing, LLCInventors: Nikitha Rao, Chetan Bansal, Zhongyan Guan, Mark Alistair Wilson-Thomas, Nachiappan Nagappan, Thomas Michael Josef Zimmermann
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Publication number: 20220107802Abstract: Embodiments promote searcher productivity and efficient search engine usage by using extraquery context to detect a searcher's intent, and using detected intent to match searches to well-suited search providers. Extraquery context may include cursor location, open files, and other editing information, tool state, tool configuration or environment, project metadata, and other information external to actual search query text. Search intent may be code (seeking snippets) or non-code (seeking documentation), and sub-intents may be distinguished for different kinds of documentation or different programming languages. Search provider capabilities may reflect input formats such as natural language or logical operator usage, or content scope such as web-wide or local, or other search provider technical characteristics.Type: ApplicationFiled: October 3, 2020Publication date: April 7, 2022Inventors: Nikitha RAO, Chetan BANSAL, Zhongyan GUAN, Mark Alistair WILSON-THOMAS, Nachiappan NAGAPPAN, Thomas Michael Josef ZIMMERMANN
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Publication number: 20220043779Abstract: A heuristics-based concurrent edit detector (“ConE”) can notify collaborators about potential conflicts that may be caused by edits made by other collaborators. ConE may compare concurrent edits submitted by collaborators, calculate the extent of overlap between two sets of edits, apply one or more filters to balance recall versus precision, and decide whether to alert the collaborators about candidate potential conflicts. ConE may be light-weight and easily scalable to work in a very large environment with numerous collaborators.Type: ApplicationFiled: August 5, 2020Publication date: February 10, 2022Applicant: Microsoft Technology Licensing, LLCInventors: Chandra Sekhar Maddila, Nachiappan Nagappan, Christian Alma Bird
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Publication number: 20220012633Abstract: Systems and methods for automatic recognition of entities related to cloud incidents are described. A method, implemented by at least one processor, for processing cloud incidents related information, including entity names and entity values associated with incidents having a potential to adversely impact products or services offered by a cloud service provider is provided. The method may include using at least one processor, processing the cloud incidents related information to convert at least words and symbols corresponding to a cloud incident into machine learning formatted data. The method may further include using a machine learning pipeline, processing at least a subset of the machine learning formatted data to recognize entity names and entity values associated with the cloud incident.Type: ApplicationFiled: July 10, 2020Publication date: January 13, 2022Inventors: Manish Shetty MOLAHALLI, Chetan BANSAL, Sumit KUMAR, Nikitha RAO, Nachiappan NAGAPPAN, Thomas Michael Josef ZIMMERMANN
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Publication number: 20220012020Abstract: A synthesis procedure learns program transformations for a text document, on-the-fly during an edit session, from examples of concrete edits made during the edit session and from an unsupervised set of additional inputs. The additional inputs are derived from explicit feedback from the user and inferred feedback from the user's behavior during the edit session. A reward score, based on anti-unification and provenance analysis, is used to classify the additional inputs as either a positive input or a negative input. Outputs are generated for the positive inputs that are consistent with the existing examples and then used to synthesize a new program transformation. The program transformations are then used to generate code edit suggestions during the edit session.Type: ApplicationFiled: September 30, 2020Publication date: January 13, 2022Inventors: SHRADDHA GOVIND BARKE, XIANG GAO, SUMIT GULWANI, ALAN THOMAS LEUNG, NACHIAPPAN NAGAPPAN, ARJUN RADHAKRISHNA, GUSTAVO ARAUJO SOARES, ASHISH TIWARI, MARK ALISTAIR WILSON-THOMAS
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Publication number: 20210117838Abstract: A computer implemented method includes receiving an exception generated based on programming code, generating exception features from the received exception, the generated exception features being generated based on a set exception features derived from search logs, and executing a machine learning model on the received exception and generated exception features to provide information from the search logs identified as most helpful to resolve the received exception, wherein the machine learning model was trained on training data comprising extracted exceptions and the set of exception features derived from the search logs.Type: ApplicationFiled: October 21, 2019Publication date: April 22, 2021Inventors: Foyzul Hassan, Chetan Bansal, Thomas Michael Josef Zimmermann, Nachiappan Nagappan, Ahmed Awadallah
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Patent number: 10235277Abstract: Identifying false test alarms to a developer. A code build is executed in a test system that includes computing functionality and computing infrastructure that is able to execute the build. Executing the code build includes running a plurality of system and integration tests on the code build. As a result of executing the code build, a system and integration test failure is identified. One or more characteristics of the system and integration test failure are identified. The characteristics of the system and integration test failure are compared to characteristics of a set of historical previous known false test alarms. False test alarms are failures caused by a factor other than a factor for which a test is being run. Based on the act of comparing, information is provided to a developer with respect to if the system and integration test failure is potentially a false test alarm.Type: GrantFiled: June 16, 2017Date of Patent: March 19, 2019Assignee: Microsoft Technology Licensing, LLCInventors: Kim Sebastian Herzig, Nachiappan Nagappan
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Publication number: 20170286276Abstract: Identifying false test alarms to a developer. A code build is executed in a test system that includes computing functionality and computing infrastructure that is able to execute the build. Executing the code build includes running a plurality of system and integration tests on the code build. As a result of executing the code build, a system and integration test failure is identified. One or more characteristics of the system and integration test failure are identified. The characteristics of the system and integration test failure are compared to characteristics of a set of historical previous known false test alarms. False test alarms are failures caused by a factor other than a factor for which a test is being run. Based on the act of comparing, information is provided to a developer with respect to if the system and integration test failure is potentially a false test alarm.Type: ApplicationFiled: June 16, 2017Publication date: October 5, 2017Inventors: Kim Sebastian HERZIG, Nachiappan NAGAPPAN
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Patent number: 9710364Abstract: Identifying false test alarms to a developer. A code build is executed in a test system that includes computing functionality and computing infrastructure that is able to execute the build. Executing the code build includes running a plurality of system and integration tests on the code build. As a result of executing the code build, a system and integration test failure is identified. One or more characteristics of the system and integration test failure are identified. The characteristics of the system and integration test failure are compared to characteristics of a set of historical previous known false test alarms. False test alarms are failures caused by a factor other than a factor for which a test is being run. Based on the act of comparing, information is provided to a developer with respect to if the system and integration test failure is potentially a false test alarm.Type: GrantFiled: September 4, 2015Date of Patent: July 18, 2017Assignee: Micron Technology Licensing, LLCInventors: Kim Sebastian Herzig, Nachiappan Nagappan
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Publication number: 20170068612Abstract: Identifying false test alarms to a developer. A code build is executed in a test system that includes computing functionality and computing infrastructure that is able to execute the build. Executing the code build includes running a plurality of system and integration tests on the code build. As a result of executing the code build, a system and integration test failure is identified. One or more characteristics of the system and integration test failure are identified. The characteristics of the system and integration test failure are compared to characteristics of a set of historical previous known false test alarms. False test alarms are failures caused by a factor other than a factor for which a test is being run. Based on the act of comparing, information is provided to a developer with respect to if the system and integration test failure is potentially a false test alarm.Type: ApplicationFiled: September 4, 2015Publication date: March 9, 2017Inventors: Kim Sebastian Herzig, Nachiappan Nagappan
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Patent number: 9400541Abstract: Techniques pertaining to analyzing power consumed by a processing unit in a mobile computing device caused by execution of certain modules are described herein. A power trace is generated that indicates an amount of power consumed by the processing unit over time, and the power trace is aligned with an execution log. Spikes are extracted from the power trace, and computing operations are performed over the spikes to acquire data pertaining to power consumed by the processing unit that are attributable to modules in the execution log.Type: GrantFiled: January 16, 2015Date of Patent: July 26, 2016Assignee: Microsoft Technology Licensing,LLCInventors: Thomas Michael Josef Zimmermann, Christian Alma Bird, Nachiappan Nagappan, Syed Masum Emran, Thirumalesh Bhat, Ashish Gupta
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Patent number: 9378015Abstract: A system is described herein that predicts defects in a portion of code of an application that is configured to execute on a computing device. Versions of code are analyzed to locate change bursts, which are alterations to at least one portion of code over time-related events. If a change burst is identified, defects are predicted with respect to the code based at least in part upon the identified change burst.Type: GrantFiled: August 11, 2009Date of Patent: June 28, 2016Assignee: Microsoft Technology Licensing, LLCInventors: Nachiappan Nagappan, Thomas Michael Josef Zimmermann, Brendan Seamus Murphy, Andreas Zeller
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Patent number: 9122490Abstract: Generation of a dependency graph for code that includes code portions such as resources or functions or both. For some or all of the nodes, the dependency is calculated by determining that the given node, a depending node, depends on an affecting node. The dependency is recorded so as to be associated with the node. Furthermore, the dependency calculation method is recorded so as to be associated with the dependency. The code may perhaps include portions within two different domains, in which the mechanism for calculating dependencies may differ. In some cases, the dependency graph may be constructed in stages, and perhaps additional properties may be associated with the node, and metadata of the properties may also be recorded.Type: GrantFiled: October 17, 2012Date of Patent: September 1, 2015Assignee: Microsoft Technology Licensing, LLCInventors: Michael C. Fanning, Christopher M. H. Faucon, Matthew Thornhill Hall, Nachiappan Nagappan, Benjamin Livshits, Magnus Madsen
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Publication number: 20150126254Abstract: Techniques pertaining to analyzing power consumed by a processing unit in a mobile computing device caused by execution of certain modules are described herein. A power trace is generated that indicates an amount of power consumed by the processing unit over time, and the power trace is aligned with an execution log. Spikes are extracted from the power trace, and computing operations are performed over the spikes to acquire data pertaining to power consumed by the processing unit that are attributable to modules in the execution log.Type: ApplicationFiled: January 16, 2015Publication date: May 7, 2015Inventors: Thomas Michael Josef Zimmermann, Christian Alma Bird, Nachiappan Nagappan, Syed Masum Emran, Thirumalesh Bhat, Ashish Gupta