Learning and using programming styles

Techniques are described herein for using artificial intelligence to "learn," statistically, a target programming style that is imposed in and/or evidenced by a code base. Once the target programming style is learned, it can be used for various purposes. In various implementations, one or...

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Bibliographic Details
Main Authors Hatalsky, Olivia, Zhang, Qianyu, Evangelopoulos, Georgios, Ni, Bin
Format Patent
LanguageEnglish
Published 05.09.2023
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:Techniques are described herein for using artificial intelligence to "learn," statistically, a target programming style that is imposed in and/or evidenced by a code base. Once the target programming style is learned, it can be used for various purposes. In various implementations, one or more generative adversarial networks ("GANs"), each including a generator machine learning model and a discriminator machine learning model, may be trained to facilitate learning and application of target programming style(s). In some implementations, the discriminator(s) and/or generator(s) may operate on graphical input, and may take the form of graph neural networks ("GNNs"), graph attention neural networks ("GANNs"), graph convolutional networks ("GCNs"), etc., although this is not required.
Bibliography:Application Number: US202117563881