Test Cases Generation for Model Transformations from Structural Information
Abstract
Most of existing approaches for test cases generation to transformation mechanisms use a main criterion which is the coverage of source and target meta-model elements. However, this criterion is not sufficient in a real-world scenario. In fact, test-cases generated to cover meta-model elements cannot detect some transformation errors due to model-scalability reasons. These generated test cases are simple and different, in general, from source models that are used in an industrial setting. To make the situation worse, source models cannot be provided by industrial companies due to security/confidentiality reasons. Instead of real data (source models), corporations can provide structural information about their source models (e.g. number of classes, number of relationships, etc.). We propose a search-based approach for generating test cases based on the coverage of structural information in addition to meta-models coverage. The validation results on a transformation mechanism used by an industrial partner confirm the effectiveness of our approach.
Recommended Citation
W. Wang et al., "Test Cases Generation for Model Transformations from Structural Information," CEUR Workshop Proceedings, vol. 1104, pp. 42 - 51, CEUR-WS, Jan 2013.
Department(s)
Computer Science
Keywords and Phrases
Model transformation; Search-based software engineering; Testing
International Standard Serial Number (ISSN)
1613-0073
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 CEUR-WS, All rights reserved.
Publication Date
01 Jan 2013