Abstract
In a complex socio-technical system, a human’s goal is delegated to many actors such as human and machines. Because the delegated goal can be decomposed into several sub-goals by each actor, goals are delegated recursively until an actor provides the means to achieve each sub-goal. We have already proposed a notation and a method called GDMA to represent and analyze the issues above. Because GDMA can be represented in a class diagram, software engineers do not have to use specific tools of GDMA models. To confirm whether a goal is properly achieved by suitable means, we have to trace such delegation and decomposition relationships. However, it is not easy to confirm it in a real-world system because of the system’s complexity. In this paper, we present a tool to check such traceability. The tool is implemented as a plugin of an existing UML modeling editor, and goal dependencies and decompositions are depicted using color. We also evaluate the tool through a comparative experiment. As a result, the tool enables an analyst to check the traceability without omission although it does not improve efficiency of the traceability checking task.
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This work was supported by JSPS KAKENHI Grant Numbers 18K11249 and 16H02804.
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Kaiya, H. et al. (2020). Experimental Evaluation of Traceability Checking Tool for Goal Dependency Modeling. In: Virvou, M., Nakagawa, H., C. Jain, L. (eds) Knowledge-Based Software Engineering: 2020. JCKBSE 2020. Learning and Analytics in Intelligent Systems, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-030-53949-8_7
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DOI: https://doi.org/10.1007/978-3-030-53949-8_7
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