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US Patent 11513773 Feedback-driven semi-supervised synthesis of program transformations

Patent 11513773 was granted and assigned to Microsoft on November, 2022 by the United States Patent and Trademark Office.

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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
115137730
Patent Inventor Names
Nachiappan Nagappan0
Xiang Gao0
Sumit Gulwani0
Alan Thomas Leung0
Arjun Radhakrishna0
Ashish Tiwari0
Gustavo Araujo Soares0
Mark Alistair Wilson-Thomas0
...
Date of Patent
November 29, 2022
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Patent Application Number
170384270
Date Filed
September 30, 2020
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Patent Citations
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US Patent 10466978 Intelligent assistant for automating recommendations for analytics programs
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US Patent 10474961 Dynamically evolving cognitive architecture system based on prompting for additional user input
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US Patent 10671355 Code completion with machine learning
Patent Citations Received
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US Patent 11782682 Providing metric data for patterns usable in a modeling environment
Patent Primary Examiner
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Ryan D. Coyer
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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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