Superstate identification for state machines using search-based clustering
Superstate identification for state machines using search-based clustering
复制标题
使用基于搜索的聚类对状态机进行超级状态识别
DOI：
10.1145/1830483.1830736
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发表时间：
2010
期刊：
影响因子：
--
通讯作者：
Hall M
中科院分区：
文献类型：
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作者：
Hall M
状态机是一种在高抽象级别上表示系统的流行方法，它使开发人员能够获得他们所表示的系统的概述并快速理解它。已经开发了几种技术来从软件中对状态机进行逆向工程，以便产生关于系统如何工作的简明和最新的文档。然而，被恢复的机器通常是扁平的，并且包含大量的状态。这意味着，他们应该提供的抽象图片往往是本身非常复杂的，需要努力理解。本文提出了使用基于搜索的聚类作为克服这个问题的一种手段。群集状态机打开了恢复状态机的结构层次的可能性，使得可以识别超状态。一个评估研究使用束搜索为基础的聚类工具，这表明该方法的实用性。
State machines are a popular method of representing a system at a high level of abstraction that enables developers to gain an overview of the system they represent and quickly understand it.Several techniques have been developed to reverse engineer state machines from software, so as to produce a concise and up-to-date document of how a system works. However, the machines that are recovered are usually flat and contain a large number of states. This means that the abstract picture they are supposed to provide is often itself very complex, requiring effort to understand.This paper proposes the use of search-based clustering as a means of overcoming this problem. Clustering state machines opens up the possibility of recovering the structural hierarchy of a state machine, such that superstates may be identified. An evaluation study is performed using the Bunch search-based clustering tool, which demonstrates the usefulness of the approach.
DOI：
10.1007/978-3-642-05089-3_20
发表时间：
2009-11
期刊：
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影响因子：
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作者：
Neil Walkinshaw;J. Derrick;Qiang Guo
通讯作者：
Neil Walkinshaw;J. Derrick;Qiang Guo
FSM 行为阶段聚类及其在 VLSI 测试中的应用
DOI：
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发表时间：
2002
期刊：
Science in China Series F: Information Sciences
影响因子：
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作者：
Huawei Li;Y. Min;Zhongcheng Li
通讯作者：
Zhongcheng Li