Alternatives To The Knowledge Discovery Metamodel: An Investigation

INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING(2017)

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摘要
To better understand and exploit the knowledge necessary to comprehend and evolve an existing system, different models can be extracted from it. Models represent the extracted information at various abstraction levels, and are useful to document, maintain, and reengineer the system. The Knowledge Discovery Metamodel (KDM) has been defined by the object management group as a meta-model supporting a large share of reverse engineering activities. Its specification has also been adopted by the ISO in 2012. This paper explores and describes alternative meta-models proposed in the literature to support reverse engineering, program comprehension, and software evolution activities. We focus on the similarity and differences of the alternative meta-models with KDM, trying to understand the potentials of reciprocal information interchange. We describe KDM and other five meta-models, plus their extensions available in the literature and their diffusion in the reverse engineering community. We also investigate the approaches using KDM and the five meta-models. In the paper, we underline the limited reuse of models for reverse engineering, and identify potential directions for future related research, to enhance the existing models and ease the exchange of information among them.
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关键词
Models, reverse engineering, model driven reverse engineering
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