Software similarity measurements using UML diagrams: A systematic literature review

Evi Triandini(1*), Reza Fauzan(2), Daniel O. Siahaan(3), Siti Rochimah(4), I Gede Suardika(5), Devi Karolita(6),

(1) Institut Teknologi dan Bisnis STIKOM Bali
(2) Politeknik Negeri Banjarmasin
(3) Institut Teknologi Sepuluh Nopember
(4) Institut Teknologi Sepuluh Nopember
(5) Institut Teknologi dan Bisnis STIKOM Bali
(6) Monash University
(*) Corresponding Author

Abstract


Every piece of software uses a model to derive its operational, auxiliary, and functional procedures. Unified Modeling Language (UML) is a standard displaying language for determining, recording, and building a software product. Several algorithms have been used by researchers to measure similarities between UML artifacts. However, there no literature studies have considered measurements of UML diagram similarities. This paper presents the results of a systematic literature review concerning similarity measurements between the UML diagrams of different software products. The study reviews and identifies similarity measurements of UML artifacts, with class diagram, sequence diagram, statechart diagram, and use case diagram being UML diagrams that are widely used as research objects for measuring similarity. Measuring similarity enables resolution of the problem domains of software reuse, similarity measurement, and clone detection. The instruments used to measure similarity are semantic and structural similarity. The findings indicate opportunities for future research regarding calculating other UML diagrams, compiling calculation information for each diagram, adapting semantic and structural similarity calculation methods, determining the best weight for each item in the diagram, testing novel proposed methods, and building or finding good datasets for use as testing material.

Keywords


software similarity; similarity measurement; UML diagram similarity; semantic similarity; structural similarity

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DOI: https://doi.org/10.26594/register.v8i1.2248

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Copyright (c) 2022 Evi Triandini, Reza Fauzan, Daniel O. Siahaan, Siti Rochimah, I Gede Suardika, Devi Karolita

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