Version 1
: Received: 30 January 2018 / Approved: 31 January 2018 / Online: 31 January 2018 (02:44:53 CET)
How to cite:
Yarushkina, N.; Guskov, G.; Dudarin, P. An Approach to Determining Software Projects with Similar Functionality and Architecture Process Based on Artificial Intelligence Methods. Preprints2018, 2018010290. https://doi.org/10.20944/preprints201801.0290.v1
Yarushkina, N.; Guskov, G.; Dudarin, P. An Approach to Determining Software Projects with Similar Functionality and Architecture Process Based on Artificial Intelligence Methods. Preprints 2018, 2018010290. https://doi.org/10.20944/preprints201801.0290.v1
Yarushkina, N.; Guskov, G.; Dudarin, P. An Approach to Determining Software Projects with Similar Functionality and Architecture Process Based on Artificial Intelligence Methods. Preprints2018, 2018010290. https://doi.org/10.20944/preprints201801.0290.v1
APA Style
Yarushkina, N., Guskov, G., & Dudarin, P. (2018). An Approach to Determining Software Projects with Similar Functionality and Architecture Process Based on Artificial Intelligence Methods. Preprints. https://doi.org/10.20944/preprints201801.0290.v1
Chicago/Turabian Style
Yarushkina, N., Gleb Guskov and Pavel Dudarin. 2018 "An Approach to Determining Software Projects with Similar Functionality and Architecture Process Based on Artificial Intelligence Methods" Preprints. https://doi.org/10.20944/preprints201801.0290.v1
Abstract
Software engineers from all over the world solve independently a lot of similar problems. In this condition the problem of code or even better architecture reusing becomes an issue of the day. In this paper two phase approach to determining the functional and structural likenesses of software projects is proposed. This approach combines two methods of artificial intelligence: natural language processing techniques with a novel method for comparing software projects based on ontological representation of their architecture automatically obtained from the projects source code. Additionally several similarity metrics are proposed to estimate similarity between projects.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.