Abstract
Goal refinement is a crucial step in goal-oriented requirements analysis to create a goal model of high quality. Poor goal refinement leads to missing requirements and eliciting incorrect requirements as well as less comprehensiveness of produced goal models. This paper proposes a technique to automate detecting bad smells of goal refinement, symptoms of poor goal refinement. Based on the classification of poor refinement, we defined four types of bad smells of goal refinement and developed two types of measures to detect them: measures on the graph structure of a goal model and semantic similarity of goal descriptions. We have implemented a support tool to detect bad smells and assessed its usefulness by an experiment.
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Acknowledgments
This work was partly supported by JSPS Grants-in-Aid for Scientific Research Nos. JP15K00088, JP15K15970, and JP15H02685. We would like to thank Prof. Takako Nakatani for giving us sample goal models having poor refinement.
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Asano, K., Hayashi, S., Saeki, M. (2017). Detecting Bad Smells of Refinement in Goal-Oriented Requirements Analysis. In: de Cesare, S., Frank, U. (eds) Advances in Conceptual Modeling. ER 2017. Lecture Notes in Computer Science(), vol 10651. Springer, Cham. https://doi.org/10.1007/978-3-319-70625-2_12
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