An Algorithm for Distance Calculation Between UML Sequence Diagrams

被引：0
|
作者：
Canal, J. [1 ]
Farias, K. [2 ]
Goncales, L. [3 ]
机构：
[1] Univ Vale Rio dos Sinos UNISINOS, Sao Leopoldo, Brazil
[2] Univ Vale Rio dos Sinos UNISINOS, Interdisciplinary Postgrad Program Appl Comp, Sao Leopoldo, Brazil
[3] Univ Vale Rio dos Sinos UNISINOS, Grad Program Appl Comp PPGCA, Sao Leopoldo, Brazil
来源：
IEEE LATIN AMERICA TRANSACTIONS | 2018年 / 16卷 / 04期
关键词：
UML; Models Distance; Levenshtein algorithm; Model Composition; Graph Edit Distance; Sequence Diagram;
D O I：
10.1109/TLA.2018.8362157
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The measure of distance between UML diagrams is a crucial step to support the integration of UML sequence diagrams. This distance is used for measuring the difference between two sequences messages exchanged by objects. Even though UML sequence diagram is widely used, nothing has been done to support to find matches for short sequence of messages in many longer interactions between objects. Unfortunately, calculating this distance is still a great challenge for developers given the problem at hand as semantic information is typically not included in any formal way in the models. Therefore, this work focuses on proposing an algorithm for calculating distance between sequence diagrams to enable an identification of similarity between models. For this, the proposed algorithm was implemented and incorporated into a model composition tool, namely MoCoTo. Our preliminary evaluation indicated that the algorithm was able to measure the distance between two UML sequence diagrams properly.
引用
收藏
页码：1200 / 1205
页数：6
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