Academic Journal
A Method for Enterprise Architecture Model Slicing
| Title: | A Method for Enterprise Architecture Model Slicing |
|---|---|
| Authors: | Hong Guo, Jingyue Li, Shang Gao, Darja Smite |
| Source: | Applied Sciences, Vol 12, Iss 19, p 9604 (2022) |
| Publisher Information: | MDPI AG, 2022. |
| Publication Year: | 2022 |
| Collection: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| Subject Terms: | enterprise architecture (EA), agile, lean, repository, program slicing, model slicing, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| More Details: | Enterprise Architecture (EA) has been applied widely in industry as it brings substantial benefits to ease communication and improve business-IT alignment. However, due to its high complexity and cost, EA still plays a limited role in many organizations. Existing research recommends realizing more of the EA potential. EA can be developed for specific purposes, accumulated in a digital repository, and reused when needed later. Due to the diversity and inconsistency of the repository, it is challenging to find relevant EA data and reuse it. In the present research, we propose using slicing techniques to extract EA models for reuse. We validate the method with an official EA repository hosted by The Open Group. The result shows that the method could facilitate extracting existing EA model components for developing new EA artifacts to save cost, alleviate maintenance effort, and help keep the repository consistent for future (re)use. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2076-3417 |
| Relation: | https://www.mdpi.com/2076-3417/12/19/9604; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app12199604 |
| Access URL: | https://doaj.org/article/0e91c731211e43e1bc6837c4db4ec471 |
| Accession Number: | edsdoj.0e91c731211e43e1bc6837c4db4ec471 |
| Database: | Directory of Open Access Journals |
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| ISSN: | 20763417 |
|---|---|
| DOI: | 10.3390/app12199604 |
| Published in: | Applied Sciences |
| Language: | English |