DETECTING SOURCE CODE FRAGMENTS SIMILARITY WITH MACHINE LEARNING ALGORITHMS
N. A. Gribkov, T. D. Ovasapyan, D. A. Moskvin Peter the Great St. Petersburg Polytechnic University (SPbPU)
Annotation: 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.
Keywords: code clones, syntactic similarity, semantic similarity, open-source software.
Pages 62-71