Title: Mining patterns in open source software using software metrics and neural network models
Authors: Ashish Kumar Dwivedi; Shashank Mouli Satapathy
Addresses: Department of Computer Science and Engineering, Gayatri Vidya Parishad College of Engineering, Visakhapatnam, 530048, India ' School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, 632014, India
Abstract: As the complexity of a system increases, the need to develop a prototype for the problems becomes more and more prominent. To take care of different plan issues, it is seen that structure design finds a superior answer for a large number of repetitive plan issues. For the most part, design-level documents are indicated utilising semi-formal documentation, for example, unified modelling language (UML) diagrams. In any case, these kinds of semi-formal documentation lead to ambiguities and irregularities. In this paper, design level documents are retrieved by using the idea of program metrics. The proposed methodology retrieves the reusable documents from the open-source software such as PMD and JUnit. The presented method uses three kinds of neural network models to analyse the effectiveness of the pattern retrieval approach.
Keywords: ANN; artificial neural network; design patterns; GRNN; generalised regression neural networks; LRNN; layer recurrent neural network; open source software; software metrics.
International Journal of System of Systems Engineering, 2020 Vol.10 No.4, pp.397 - 409
Received: 18 Apr 2020
Accepted: 10 Jul 2020
Published online: 07 Jan 2021 *