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	Active Learning from Blackbox to Timed Connectors
	Li, Yi ; Sun, Meng ; Wang, Yiwu
	2016
关键词	Active Learning Coordination Connectors
英文摘要	Coordination models and languages play a key role in formally specifying the communication and interaction among different components in large-scale concurrent systems. In this paper, we use active learning to extract timed connector models from black-box system implementations. Firstly, parameterized Mealy machine (PMM) is introduced as an operational semantic model for channel-based coordination language Reo. With product and link operators defined, we can construct complex connectors by joining basic ones in form of PMM. Moreover, with a concretize mapping function, PMMs can be easily transformed into Mealy machines, and the latter can be extracted by an optimized L* algorithm.; EI; CPCI-S(ISTP); liyi_math@pku.edu.cn; summeng@math.pku.edu.cn; yiwuwang@126.com; 132-135
语种	英语
出处	SCI ; EI
出版者	10th International Symposium on Theoretical Aspects of Software Engineering (TASE)
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/449358]
专题	数学科学学院
推荐引用方式 GB/T 7714	Li, Yi,Sun, Meng,Wang, Yiwu. Active Learning from Blackbox to Timed Connectors. 2016-01-01.

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