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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 7 Issue 5, 2016.
Abstract: Model defects are a significant concern in the Model-Driven Development (MDD) paradigm, as model trans-formations and code generation may propagate errors present in the model to other notations where they are harder to detect and trace. Formal verification techniques can check the correctness of a model, but their high computational complexity can limit their scalability. Current approaches to this problem have an exponential worst-case run time. In this paper, we propose a slicing technique which breaks a model into several independent submodels from which irrelevant information can be abstracted to improve the scalability of the verification process. We consider a specific static model (UML class diagrams annotated with unrestricted OCL constraints) and a specific property to verify (satisfiability, i.e., whether it is possible to create objects without violating any constraints). The definition of the slicing procedure ensures that the property under verification is preserved after partitioning. Furthermore, the paper provides an evaluation of experimental results from a real-world case study.
Asadullah Shaikh and Uffe Kock Wiil, “Efficient Verification-Driven Slicing of UML/OCL Class Diagrams” International Journal of Advanced Computer Science and Applications(IJACSA), 7(5), 2016. http://dx.doi.org/10.14569/IJACSA.2016.070571
@article{Shaikh2016,
title = {Efficient Verification-Driven Slicing of UML/OCL Class Diagrams},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2016.070571},
url = {http://dx.doi.org/10.14569/IJACSA.2016.070571},
year = {2016},
publisher = {The Science and Information Organization},
volume = {7},
number = {5},
author = {Asadullah Shaikh and Uffe Kock Wiil}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.