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Dealing with goal models complexity using topological metrics and algorithms

Author
Méndez, L.; López, L.; Ayala, C.P.
Type of activity
Presentation of work at congresses
Name of edition
10th International i* Workshop
Date of publication
2018
Presentation's date
2017-06-12
Book of congress proceedings
iStar 2017: Proceedings of the 10th International i* Workshop co-located with the 29th International Conference on Advanced Information Systems Engineering (CAiSE 2017): Essen, Germany, June 12-13, 2017
First page
43
Last page
48
Publisher
CEUR-WS.org
Project funding
Quality-Aware Rapid Software Development (Q-RAPIDS)
Repository
http://hdl.handle.net/2117/119981 Open in new window
URL
http://ceur-ws.org/Vol-1829/iStar17_paper_3.pdf Open in new window
Abstract
The inherent complexity of business goal-models is a challenge for organizations that has to analyze and maintaining them. Several approaches are developed to reduce the complexity into manageable limits, either by providing support to the modularization or designing metrics to monitor the complexity levels. These approaches are designed to identify an unusual complexity comparing it among models. In the present work, we expose two approaches based on structural characteristics of goal-model, wh...
Citation
Méndez, L., López, L., Ayala, C.P. Dealing with goal models complexity using topological metrics and algorithms. A: International i* Workshop. "iStar 2017: Proceedings of the 10th International i* Workshop co-located with the 29th International Conference on Advanced Information Systems Engineering (CAiSE 2017): Essen, Germany, June 12-13, 2017". CEUR-WS.org, 2017, p. 43-48.
Keywords
Clustering, Complexity, Metrics, PageRank, i* Framework, iStar
Group of research
GESSI - Group of Software and Service Engineering
inSSIDE - integrated Software, Service, Information and Data Engineering

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