DETECTING SOURCE CODE FRAGMENTS SIMILARITY WITH MACHINE LEARNING ALGORITHMS

The paper proposes a method for detecting source code fragments similarity using attribute
abstract syntax trees and machine learning algorithms. The advantages of the method are
determined based on a comparative analysis of existing approaches of detecting code clones. For
approaches, which use AST, it is possible to increase the efficiency of detecting similar source code
fragments by detecting semantic clones with usage of method proposed.