Automation of Software Code Analysis Using Machine Learning Methods.

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Titel: Automation of Software Code Analysis Using Machine Learning Methods.
Autoren: Moshkin, V. S., Dyrnochkin, A. A., Yarushkina, N. G.
Quelle: Pattern Recognition & Image Analysis; Sep2023, Vol. 33 Issue 3, p417-424, 8p
Abstract: The paper presents a description of the developed approach and service for the intelligent analysis of source code in Python. The service reduces the time of code verification by partial automation. The FastText algorithm is used to obtain vector representations of source code texts. A pretrained neural network language model based on the transformer architecture was used to obtain a possible assignment of a natural language function. A classifier based on the gradient enhancement algorithm was used to detect repetitive headers. The developed service checks the set of changes and publishes error reports and duplicates in the format of comments of the set of changes after publishing the set of changes in the remote Git repository. [ABSTRACT FROM AUTHOR]
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Datenbank: Complementary Index
Beschreibung
Abstract:The paper presents a description of the developed approach and service for the intelligent analysis of source code in Python. The service reduces the time of code verification by partial automation. The FastText algorithm is used to obtain vector representations of source code texts. A pretrained neural network language model based on the transformer architecture was used to obtain a possible assignment of a natural language function. A classifier based on the gradient enhancement algorithm was used to detect repetitive headers. The developed service checks the set of changes and publishes error reports and duplicates in the format of comments of the set of changes after publishing the set of changes in the remote Git repository. [ABSTRACT FROM AUTHOR]
ISSN:10546618
DOI:10.1134/S1054661823030318