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An Automated Change Impact Analysis Approach to GRL Models

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SDL 2017: Model-Driven Engineering for Future Internet (SDL 2017)

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Abstract

Goal-oriented approaches to requirements engineering have gained momentum with the development of many frameworks, methods, and tools. As stakeholders’ needs evolve, goal models evolve quickly and undergo many changes in order to accommodate the rapid changes of stakeholders’ goals, technologies, and business environments. Therefore, there is a need for mechanisms to identify and analyze the impact of changes in goal models. In this paper, we propose a Change Impact Analysis (CIA) approach to Goal-oriented Requirements Language (GRL), part of ITU-T’s User Requirement Notation (URN) standard. Given a suggested modification within a given GRL model, our approach allows for the identification of all impacted GRL elements within the targeted model as well as across all GRL models that are linked to it through URN Links. Furthermore, the proposed approach allows for the identification of the potentially impacted GRL evaluation strategies. The developed GRL-based CIA approach is implemented as a feature within the Eclipse-based jUCMNav framework. We demonstrate the applicability of our approach using two real-world GRL specifications.

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Notes

  1. 1.

    The CIA feature is publicly available and can be downloaded from https://github.com/JUCMNAV/projetseg/tree/grl.

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Acknowledgment

The authors would like to acknowledge the support provided by the Deanship of Scientific Research at King Fahd University of Petroleum & Minerals for funding this work through project No. FT151004.

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Correspondence to Jameleddine Hassine .

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Alkaf, H.S., Hassine, J., Hamou-Lhadj, A., Alawneh, L. (2017). An Automated Change Impact Analysis Approach to GRL Models. In: Csöndes, T., Kovács, G., Réthy, G. (eds) SDL 2017: Model-Driven Engineering for Future Internet. SDL 2017. Lecture Notes in Computer Science(), vol 10567. Springer, Cham. https://doi.org/10.1007/978-3-319-68015-6_10

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  • DOI: https://doi.org/10.1007/978-3-319-68015-6_10

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