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A Service Composition Approach Based on sequence mining for Migrating E-learning Legacy System to SOA

International Journal of Automation and computing 2010年第4期7卷 584-595页

作者： Zhuo Zhang Dong-Dai Zhou Hong-Ji Yang Shao-Chun Zhong Software School in Northeast Normal University Changchun 130024 PRC Software Technology Research Laboratory De Montfort University Leicester LE1 9BH UK Institute of Ideal Information and Technology in Northeast Normal University Changchun 130024 PRC Engineering Research Center of E-Learning Technologies Ministry of Education Changchun 130024 PRC

With the fast development of business logic and information technology, today＇s best solutions are tomorrow＇s legacy systems. In China, the situation in the education domain follows the same path. Currently, there exists a number of e-learning legacy assets with accumulated practical business experience, such as program resource, usage behaviour data resource, and so on. In order to use these legacy assets adequately and efficiently, we should not only utilize the explicit assets but also discover the hidden assets. The usage behaviour data resource is the set of practical operation sequences requested by all users. The hidden patterns in this data resource will provide users＇ practical experiences, which can benefit the service composition in service-oriented architecture （SOA） migration. Namely, these discovered patterns will be the candidate composite services （coarse-grained） in SOA systems. Although data mining techniques have been used for software engineering tasks, little is known about how they can be used for service composition of migrating an e-learning legacy system （MELS） to SOA. In this paper, we propose a service composition approach based on sequence mining techniques for MELS. Composite services found by this approach will be the complementation of business logic analysis results of MELS. The core of this approach is to develop an appropriate sequence mining algorithm for mining related data collected from an e-learning legacy system. According to the features of execution trace data on usage behaviour from this e-learning legacy system and needs of further pattern analysis, we propose a sequential mining algorithm to mine this kind of data of tile legacy system. For validation, this approach has been applied to the corresponding real data, which was collected from the e-learning legacy system; meanwhile, some investigation questionnaires were set up to collect satisfaction data. The investigation result is 90% the same with the result obtained thr

关键词： Service composition e-learning sequence mining algorithm service-oriented architecture (SOA) legacy system

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