基于描述逻辑的特征模型  

Feature Model Based on Description Logics

作　　者：范少锋[1] 张乃孝[1] 赵新宇[1] 

机构地区：[1]北京大学信息科学系,北京100871

出　　处：《计算机科学》2007年第1期21-25,共5页Computer Science

基　　金：国家自然科学基金项目(编号60473056资助

摘　　要：由于特征模型缺乏严格语义基础,难以对模型进行一致性推理,无法保证模型的一致性,进而影响最终软件产品的质量。本文讨论了如何使用描述逻辑对特征模型进行形式化,给出了将特征模型转化为描述逻辑ALCQI知识库的算法,通过验证转化后的知识库的一致性得到所对应特征模型的一致性。并利用描述逻辑的推理机RACER对转换得到的知识库进行推理,自动完成特征模型的一致性检查,为特征模型的一致性检验提供一种方法,实践证明这种方法具有可靠性和高效性。It is rather difficult to perform consistency reasoning on feature models since they lack the formal semantics. Without guaranteed consistency of the feature models, the quality of the software products, based on the feature models, can not be guaranteed. In this paper, how to formalize feature models with Description Logics is investigated. Following the translation principles, each feature model can be formalized into an ALCQI knowledge base. Hence the consistency reasoning on the feature model turns into the consistency reasoning on the corresponding ALCQI knowledge base. Especially, the latter reasoning can be automatically performed via the description logic reasoner RACER. It has been proven that this approach can not only improve the reasoning efficiency but also enhance the reliability.

关 键 词：描述逻辑 特征模型 一致性 RACER 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]