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US Patent 11836068 System and method for recommending static analysis fixes

Patent 11836068 was granted and assigned to Parasoft on December, 2023 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
Parasoft
Parasoft
1
Current Assignee
Parasoft
Parasoft
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
118360681
Patent Inventor Names
Leonid Borodaev1
Leszek Jerzy Raszka1
Date of Patent
December 5, 2023
1
Patent Application Number
175744661
Date Filed
January 12, 2022
1
Patent Citations
‌
US Patent 11537506 System for visually diagnosing machine learning models
1
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US Patent 10395041 Methods and systems for reducing false positive findings
1
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US Patent 10649882 Automated log analysis and problem solving using intelligent operation and deep learning
1
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US Patent 11200144 Refinement of static analysis of program code
1
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US Patent 11429360 Computer assisted programming with targeted visual feedback
1
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US Patent 11748667 Methods and systems for the measurement of relative trustworthiness for technology enhanced with AI learning algorithms
1
Patent Primary Examiner
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Matthew M Kim
1
CPC Code
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G06F 11/327
1
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G06N 20/00
1
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G06F 11/0772
1
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G06F 11/3616
1
Patent abstract

System and method for recommending static analysis fixes in a computer program include: receiving violations from a static analysis tool and the meta data related to the violations; for each violation, encoding a code snippet in which said each violation is located into a first vector and encoding meta-data associated with each violation into a second vector; for each violation, concatenating the first vector and the second vector into a single vector; generating a utility matrix from the single vectors, where values in each cell correspond to a certain user's action on one of the violations; revising the utility matrix, based on user selection of selected violations of the plurality of violations; and executing a matrix factorization process to build intermediate representations of users and sets of violations to update the utility matrix as an updated utility matrix to obtain predictions for missing values, as recommendation to the user.

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