John Yen, Xiaoqing Frank Liu and Swee Hor Teh, "A fuzzy logic-based methodology for the acquisition and analysis of imprecise requirements", The International Journal of Concurrent Engineering: Research and Application (CERA), Vol. 2, No.4, pp. 265-277, December, 1994.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....in a CE environment. There is a lack of traceability of the requirements and insufficient decomposition of requirements [14] Requirements generated by different members in a concurrent engineering team may be contradictory since different authors may have different perspectives on the system [19]. Authors of requirements use different terminology and hence the same term is applied to different concepts and different terms are used to denoted the same entity. Requirements are also changed frequently during the design process due to the changes of technology and customer s objectives [8] ....

Yen, J., Liu, X. and Teh, S. H. A fuzzy logic-based methodology for the acquisition and analysis of imprecise requirements. Concurrent Engineering: Research and Applications (1994) 2, 265-277.

....in a CE environment. There is a lack of traceability of the requirements and insufficient decomposition of requirements [12] Requirements generated by different members in a concurrent engineering team may be contradictory since different authors may have different perspectives on the system [16]. Authors of requirements use different terminology and hence the same term is applied to different concepts and different terms are used to denoted the same entity. Requirements are also changed frequently during the design process due to the changes of technology and customer s objectives [6] ....

Yen, J., Liu, X. and Teh, S. H. A fuzzy logic-based methodology for the acquisition and analysis of imprecise requirements. Concurrent Engineering: Research and Applications (1994) 2, 265-277. Wiley and Sons, New York.

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John Yen, Xiaoqing Frank Liu and Swee Hor Teh, "A fuzzy logic-based methodology for the acquisition and analysis of imprecise requirements", The International Journal of Concurrent Engineering: Research and Application (CERA), Vol. 2, No.4, pp. 265-277, December, 1994.

....the underlying representation of imprecise requirements, and (3) for assessing the priorities of conflicting requirements. We illustrate these techniques using the requirements of a conference room scheduling system. 1 Introduction There are at least two challenges with requirement engineering [1, 2]. First, requirements are usually vague and imprecise in nature. Computer based analysis, however, requires an explicit formal semantics [3] Therefore, there is a need to bridge the gap between imprecise requirements and formal specification methods. Actually, as Balzer et al. pointed out, ....

....requirement R. In our framework, the canonical form in Zedah s test score semantics is used as a basis for expressing imprecise requirements [11, 12] The representation of imprecise requirements on a system development process in canonical form is established by the following definition [2, 1]. Definition 1 Let R be an imprecise requirement on system development process in canonical form R : A i (p) is B; where p is a system development process, Sat R1 Sat R2 0 1 Satisfaction Degree of Process (a) Completely conflicting 0 1 Process Degree of Satisfaction Sat Sat R1 R2 (b) ....

J. Yen, X. Liu, and S. H. Teh, "A fuzzy logicbased methodology for the acquisition and analysis of imprecise requirements," Concurrent Engineering: Research and Applications, no. 2, pp. 265--277, 1994.

....can be generated for different cases, an overall requirement can be obtained using AV ERAGE operator as follows: ffl The average negative impact of treatment recommendations should be low. For more discussion about the formal representation of imprecise requirements, readers can refer to [14, 17, 18]. 2.2 Specifying imprecise requirements of a Conference Room Scheduling System (CRSS) Suppose that we are going to develop a conference room scheduler. The imprecise requirements for this project fall into the following three categories: 1. requirements for the scheduling system development ....

....R 0 i Omega : Omega Rn , where Omega is a fuzzy compromise operator. Assume that R i is strenthened to R 0 i . Then, F easibility(R 0 ) F easibility(R) This theorem can be proved directly based on the definition of feasibility and the property of monotonicity of compromise operator [17, 18]. It is necessary to assess the impact of changing a requirement on the satisfiability of other requirements. We are particularly interested in the impact of changing the priority of a requirement on the satisfiability of other requirements. Intuitively, reducing the priority of a requirement ....

John Yen, Xiaoqing Frank Liu and Swee Hor Teh, "A fuzzy logic-based methodology for the acquisition and analysis of imprecise requirements", The International Journal of Concurrent Engineering: Research and Application (CERA), Vol. 2, No.4, pp. 265-277, December, 1994.

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