Abstract
Reverse engineering is a very efficient way to extract automatically behavioral models from legacy systems. This paper proposes a new approach to detect and decipher dynamic information from these systems in order to recover the corresponding sequence diagram. The approach is composed of three steps: trace generation and collection, trace merging using Colored Petri Nets and sequence diagram extraction. Our results show that this approach can produce a more accurate high-level sequence diagram with main operators: “seq”, “alt”, opt” and “par”.
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Acknowledgements
We would like to thank the FST Errachidia for providing us with assist us in the development part of our research. Our sincere thanks also go to Moulay Ismail University for its financial support of the project “Algorithmic and software support for transformational approaches to UML”.
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Baidada, C., Bouziane, E.M., Jakimi, A. (2018). A Dynamic Analysis for Reverse Engineering of Sequence Diagram Using CPN. In: Abdelwahed, E., Bellatreche, L., Golfarelli, M., Méry, D., Ordonez, C. (eds) Model and Data Engineering. MEDI 2018. Lecture Notes in Computer Science(), vol 11163. Springer, Cham. https://doi.org/10.1007/978-3-030-00856-7_22
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