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DOI: 10.14569/IJACSA.2020.0111213
PDF

Recovering UML2 Sequence Diagrams from Execution Traces

Author 1: EL Mahi BOUZIANE
Author 2: Chafik BAIDADA
Author 3: Abdeslam JAKIMI

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 12, 2020.

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Abstract: Reverse engineering is a proven and efficient technique for automatically generating UML2 models from object-oriented legacy systems with missing or obsolete documentation. To perform reverse engineering, two techniques are used: dynamic and static analysis. Dynamic analysis refers to collecting information when the system is running while static analysis corresponds to inspecting the source code. Dynamic analysis is preferred than static one in order to extract dynamic models that represents the behavior of a systems because of polymorphism and dynamic binding. In this paper, we present new different methodology that use Colored Petri Nets (CPNs) to recover UML2 Sequence Diagram (SD). First, it generates execution traces corresponding to the different scenarios representing the system behavior. Then, CPNs are used to model and analyze these execution traces to extract UML2 sequence diagram. Our case study illustrates the process of our approach and show that sequence diagram can be extracted with a good accuracy.

Keywords: Execution traces; Reverse engineering; UML2; Sequence Diagram; Colored Petri Nets

EL Mahi BOUZIANE, Chafik BAIDADA and Abdeslam JAKIMI, “Recovering UML2 Sequence Diagrams from Execution Traces” International Journal of Advanced Computer Science and Applications(IJACSA), 11(12), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111213

@article{BOUZIANE2020,
title = {Recovering UML2 Sequence Diagrams from Execution Traces},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111213},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111213},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {12},
author = {EL Mahi BOUZIANE and Chafik BAIDADA and Abdeslam JAKIMI}
}



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.

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