36th International Conference on Software Engineering (ICSE Companion 2014), May 31 – June 7, 2014, Hyderabad, India

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Human Inputs in Software Engineering and Adaptation
New Ideas and Emerging Results
MR.1.3-4, Chair: Lilliana Pasquale
Modeling Self-Adaptive Software Systems with Learning Petri Nets
Zuohua Ding, Yuan Zhou, and MengChu Zhou
(Zhejiang Sci-Tech University, China; New Jersey Institute of Technology, USA)
Publisher's Version
Abstract: Traditional models have limitation to model adaptive software systems since they build only for fixed requirements, and cannot model the behaviors that change at run-time in response to environmental changes. In this paper, an adaptive Petri net is proposed to model a self-adaptive software system. It is an extension of hybrid Petri nets by embedding a neural network algorithm into them at some special transitions. The proposed net has the following advantages: 1) It can model a runtime environment; 2) The components in the model can collaborate to make adaption decisions; and 3) The computing is done at the local, while the adaption is for the whole system. We illustrate the proposed adaptive Petri net by modeling a manufacturing system.


Time stamp: 2019-12-13T07:15:32+01:00