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General Information
    • ISSN: 2382-6185
    • Abbreviated Title: Int. J. Knowl. Eng.
    • Frequency: Semiyearly
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Nina Lee
    • Indexed by: Google Scholar, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2016 Vol.2(1): 60-63 ISSN: 2382-6185
doi: 10.18178/ijke.2016.2.1.053

Workflow Design Optimization Based on Software Design

Wei Jiayuan, Guo Cong, and Zhou Quan
Abstract—Recently, the work flow management system has been widely used in the research and development project management and office automation fields. Demand for business department workflow system is increasing. In the process design for business department, some specific rules are usually contained, which vary with the variation of management. Thus with even a small modification is the rules the process design document must be re-built, It will be more costly if this is realized by modifying back-end code. To improve the expansibility of workflow system, a method is presented in this paper by abstracting business rules, custom vocabularies and rules to achieve matrix-form rule management. This method simplifies the complex logic implemented in the process design, and visualizes the realization of business logic through the business rule designer, which is more understandable in the business perspective.

Index Terms—Business rules, management, rules engine, workflow.

Wei Jiayuan and Zhou Quan are with the National Key Laboratory of Science and Technology on space Microwave, China Academy of Space Technology, Xi’an, 710100, China (e-mail: weijy@cast504.com).
Guo Cong is with Hangzhou Hollysys Automation Co., Ltd. Xi’an Branch, 710000, China (e-mail: guocong9527@163.com).


Cite: Wei Jiayuan, Guo Cong, and Zhou Quan, "Workflow Design Optimization Based on Software Design," International Journal of Knowledge Engineering vol. 2, no. 1, pp. 60-63, 2016.

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