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US Patent 10585780 Enhancing software development using bug data

Patent 10585780 was granted and assigned to Microsoft on March, 2020 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent
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Patent attributes

Patent Applicant
Microsoft
Microsoft
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Current Assignee
Microsoft
Microsoft
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Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
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Patent Number
105857800
Patent Inventor Names
Yuanyuan Dong0
Muiris Woulfe0
Poornima Muthukumar0
Date of Patent
March 10, 2020
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Patent Application Number
154693960
Date Filed
March 24, 2017
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Patent Citations
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US Patent 10175979 Defect ownership assignment system and predictive analysis for codebases
Patent Citations Received
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US Patent 11966721 Extended reality platform and machine learning engine for automated code error resolution
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US Patent 11710090 Machine-learning models to assess coding skills and video performance
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US Patent 11301358 Using false positives to detect incorrectly updated code segments
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US Patent 11334351 Systems and methods for software quality prediction
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US Patent 11893387 Systems and methods for software quality prediction
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US Patent 11914976 Three-dimensional software code review engine
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US Patent 11966326 Development test automation framework
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US Patent 10885448 Usability data analysis platform
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Patent Primary Examiner
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Francisco J Aponte
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Patent abstract

For each detected bug, historical code with similar characteristics and bug corrections from a historical bug dataset can be displayed in a source code editor. Relevant training and/or testing data can be found by comparing an internal representation of the code under development with an internal representation of the original buggy code in the historical bug dataset. Training and/or testing data that is relevant to the current code can be distinguished from irrelevant training and/or testing data by determining that the code syntax tokens from the current and historical data overlap to at least a specified percentage. Code can be devolved into a set of metrics. The degree of overlap between the metric sets can be determined. If a computed risk factor for the bug correction meets or exceeds a specified threshold, the bug correction can be automatically applied. Additional testing can be automatically performed on and/or added to the corrected code.

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