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US Patent 11765193 Contextual embeddings for improving static analyzer output

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Contents

Is a
Patent
Patent

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11765193
Patent Inventor Names
Alessandro Morari
Yunhui Zheng
Jeffrey Scott McCarley
Luca Buratti
Mihaela Ancuta Bornea
Jim Alain Laredo
Saurabh Pujar
Date of Patent
September 19, 2023
Patent Application Number
17138408
Date Filed
December 30, 2020
Patent Citations
‌
US Patent 10394687 Method for classifying alarm types in detecting source code error and nontransitory computer readable recording medium therefor
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US Patent 10558554 Machine learning based software correction
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US Patent 10705795 Duplicate and similar bug report detection and retrieval using neural networks
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US Patent 10740216 Automatic bug classification using machine learning
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US Patent 10713145 Automated debugging with combined static and dynamic analysis
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US Patent 11620515 Multi-task knowledge distillation for language model
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US Patent 8806441 Static code analysis
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US Patent 10002064 Static analysis based efficient elimination of false positive
Patent Primary Examiner
‌
Abiy Getachew
CPC Code
‌
G06F 8/51
‌
G06K 9/6267
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H04L 63/1433
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H04L 63/20
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G06K 9/6259
Patent abstract

In a computer-implemented method for improving a static analyzer output, a processor receives a labeled data set with labeled true vulnerabilities and labeled false vulnerabilities. A processor receives pretrained contextual embeddings from a contextual embeddings model. A processor maps the true vulnerabilities and the false vulnerabilities to the pretrained contextual embeddings model. A processor generates a fine-tuned model with classifications for true vulnerabilities.

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