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公开(公告)号：US11599814B2
公开(公告)日：2023-03-07
申请号：US16659174
申请日：2019-10-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Foyzul Hassan , Chetan Bansal , Thomas Michael Josef Zimmermann , Nachiappan Nagappan , Ahmed Awadallah
IPC: G06F16/9532 , G06N20/00 , G06F8/41 , G06N7/00
Abstract: 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.
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公开(公告)号：US20210117838A1
公开(公告)日：2021-04-22
申请号：US16659174
申请日：2019-10-21
Applicant: Microsoft Technology Licensing, LLC
Inventor： Foyzul Hassan , Chetan Bansal , Thomas Michael Josef Zimmermann , Nachiappan Nagappan , Ahmed Awadallah
IPC: G06N7/00 , G06N20/00 , G06F16/9532
Abstract: 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.
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公开(公告)号：US11875233B2
公开(公告)日：2024-01-16
申请号：US16925453
申请日：2020-07-10
Applicant: Microsoft Technology Licensing, LLC
Inventor： Manish Shetty Molahalli , Chetan Bansal , Sumit Kumar , Nikitha Rao , Nachiappan Nagappan , Thomas Michael Josef Zimmermann
IPC: G06N20/00 , G06F40/284 , H04L41/50 , G06F18/214
CPC classification number: G06N20/00 , G06F18/2155 , G06F40/284 , H04L41/50
Abstract: 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.
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公开(公告)号：US20230076610A1
公开(公告)日：2023-03-09
申请号：US17988580
申请日：2022-11-16
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chandra Sekhar Maddila , Nachiappan Nagappan , Christian Alma Bird
IPC: G06F16/178 , G06F8/71 , H04L67/55 , H04L67/50
Abstract: 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.
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公开(公告)号：US11513773B2
公开(公告)日：2022-11-29
申请号：US17038427
申请日：2020-09-30
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC.
Inventor： Shraddha Govind Barke , Xiang Gao , Sumit Gulwani , Alan Thomas Leung , Nachiappan Nagappan , Arjun Radhakrishna , Gustavo Araujo Soares , Ashish Tiwari , Mark Alistair Wilson-Thomas
Abstract: 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.
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Patent Agency Ranking
公开(公告)号：US09710364B2
公开(公告)日：2017-07-18
申请号：US14845891
申请日：2015-09-04
Applicant: Microsoft Technology Licensing, LLC
Inventor： Kim Sebastian Herzig , Nachiappan Nagappan
CPC classification number: G06F11/3672 , G06F11/3692
Abstract: 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.
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公开(公告)号：US11822518B2
公开(公告)日：2023-11-21
申请号：US17988580
申请日：2022-11-16
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chandra Sekhar Maddila , Nachiappan Nagappan , Christian Alma Bird
IPC: G06F16/178 , G06F8/71 , H04L67/55 , H04L67/50
CPC classification number: G06F16/1787 , G06F8/71 , H04L67/535 , H04L67/55
Abstract: 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.
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公开(公告)号：US20150126254A1
公开(公告)日：2015-05-07
申请号：US14598665
申请日：2015-01-16
Applicant: Microsoft Technology Licensing, LLC
Inventor： Thomas Michael Josef Zimmermann , Christian Alma Bird , Nachiappan Nagappan , Syed Masum Emran , Thirumalesh Bhat , Ashish Gupta
CPC classification number: G06F1/3206 , G06F1/3268 , G06F3/0625 , H04W52/0254 , H04W52/0258 , H04W52/0261 , Y02D70/142 , Y02D70/164
Abstract: 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.
Abstract translation: 本文描述了关于分析由执行某些模块引起的移动计算设备中的处理单元消耗的功率的技术。 生成指示处理单元随时间消耗的功率量的功率跟踪，并且功率跟踪与执行日志对齐。 从电力跟踪中提取尖峰，并且通过尖峰执行计算操作以获取归因于执行日志中的模块的与处理单元所消耗的功率有关的数据。
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公开(公告)号：US11550758B2
公开(公告)日：2023-01-10
申请号：US16985919
申请日：2020-08-05
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chandra Sekhar Maddila , Nachiappan Nagappan , Christian Alma Bird
IPC: H04L67/55 , G06F16/178 , G06F8/71 , H04L67/50
Abstract: 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.
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公开(公告)号：US11379227B2
公开(公告)日：2022-07-05
申请号：US17062581
申请日：2020-10-03
Applicant: Microsoft Technology Licensing, LLC
Inventor： Nikitha Rao , Chetan Bansal , Zhongyan Guan , Mark Alistair Wilson-Thomas , Nachiappan Nagappan , Thomas Michael Josef Zimmermann
IPC: G06F9/44 , G06F8/77 , G06F16/953 , G06N20/00 , G06F16/2453
Abstract: 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. Search intent detection permits efficient and effective use of a single search box for a wide variety of different searches for different kinds of results, thereby simplifying a development tool user interface.
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