描述逻辑在KBSE系统中的使用

Premkumar T. Devanbu, M. Jones
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引用次数: 53

摘要

随着许多软件系统的规模和复杂性的增加,需要在软件开发过程的许多不同层次上更加强调获取和维护知识。基于知识的软件工程(KBSE)研究范式关注的是使用正式表示的知识和相关的推理过程来支持软件开发的各种子活动的系统。随着规模的增长,KBSE系统必须在表达能力和推理能力与知识库构建、维护、性能和可理解性的实际需求之间取得平衡。描述逻辑(DL’s)具有几个特征——术语导向、形式语义和有效的推理过程——它们提供了这些因素的有效权衡。我们讨论了三个KBSE系统,其中DL获取了一些支持设计、编码和测试活动所需的必要知识。最后,我们将讨论深度学习的好处以及解决其局限性的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The use of description logics in KBSE systems
The increasing size and complexity of many software systems demand a greater emphasis on capturing and maintaining knowledge at many different levels within the software development process. The knowledge-based software engineering (KBSE) research paradigm is concerned with systems that use formally represented knowledge, with associated inference procedures, to support the various subactivities of software development. As they grow in scale, KBSE systems must balance expressivity and inferential power with the real demands of knowledge base construction, maintenance, performance and comprehensibility. Description logics (DL's) possess several features - a terminological orientation, a formal semantics and efficient reasoning procedures - which offer an effective tradeoff of these factors. We discuss three KBSE systems in which DL's capture some of the requisite knowledge needed to support design, coding and testing activities. We close with a discussion of the benefits of DL's and ways to address some of their limitations.<>
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