Business Component Identification Method Based on Semantic Similarity and the Cluster Algorithm

DOI

10.2991/edep-18.2018.66How to use a DOI?

Keywords

Reusable business component, component identification, semantic similarity, cluster algorithm.

Abstract

Component identification is a key problem in software reuse. In order to obtain a set of business components (BCs) with high reuse value and good reuse performance to support reuse, a BC design method based on the cluster algorithm was proposed. Through analyzing existing business models, element composite models were described to divide the domain by analyzing the conception semantics of the transaction field. The hierachical clustering analysis technique based on the similarity degree among activities was also given. In the identification process, the concept of business element similarity which can overcome the limitation of the domain platform was given. Commonality, variability, granularity, and reuse cost were taken into account in the method. Experiment results show that the valuation and performance of reusability for the transaction component are improved effectively, especially the design in the platform independent model.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Li-Yan CHEN
AU  - Long TAN
AU  - Jun LU
PY  - 2018/10
DA  - 2018/10
TI  - Business Component Identification Method Based on Semantic Similarity and the Cluster Algorithm
BT  - Proceedings of the 2018 International Conference on Energy Development and Environmental Protection (EDEP 2018)
PB  - Atlantis Press
SP  - 427
EP  - 433
SN  - 2352-5401
UR  - https://doi.org/10.2991/edep-18.2018.66
DO  - 10.2991/edep-18.2018.66
ID  - CHEN2018/10
ER  -