Abstract
Analytical requirements are the basis for building the enterprise data models that are used to develop the IT assets that deliver the analytical requirements to business users [10]. Due to the difficulties existed in the modeling and analysis process, reusing existing analysis experiences becomes a good choice to find an optimal way from problem domain to solution domain efficiently. To help data analysts use previous experience to elicit and model analytical requirements and find satisfactory solutions, an analysis pattern driven analytical requirements modeling method is proposed. It utilizes analysis patterns to help analysts model the relationships between data domains and machine domains, and select available analysis models under the guidance of measurable analytical goals. The modeling process is an interactive and iterative process, which uses the feedbacks from analysts to adjust its analysis behavior on real time. To illustrate the method more specifically, we apply it on requirements tracing.
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Acknowledgments
This work is supported by the National Key Research and Development Plan of China under Grant No. 2016YFB0501801, National Natural Science Foundation of China under Grant No. 61170026 and the National Standard Research Project under Grant No. 2016BZYJ-WG7-001.
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Ji, J., Peng, R. (2016). An Analysis Pattern Driven Analytical Requirements Modeling Method. In: Zhang, L., Xu, C. (eds) Software Engineering and Methodology for Emerging Domains. NASAC 2016. Communications in Computer and Information Science, vol 675. Springer, Singapore. https://doi.org/10.1007/978-981-10-3482-4_1
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DOI: https://doi.org/10.1007/978-981-10-3482-4_1
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