@inproceedings{5fee1c507ef544ce9f4a8b3e77f2949f,
title = "Modeling self-adaptive software systems with learning petri nets",
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.",
keywords = "Adaptive Petri net, Adaptive software system, Neural network, Requirement modeling",
author = "Zuohua Ding and Yuan Zhou and Zhou, \{Meng Chu\}",
year = "2014",
doi = "10.1145/2591062.2591113",
language = "English (US)",
isbn = "9781450327688",
series = "36th International Conference on Software Engineering, ICSE Companion 2014 - Proceedings",
publisher = "Association for Computing Machinery",
pages = "464--467",
booktitle = "36th International Conference on Software Engineering, ICSE Companion 2014 - Proceedings",
note = "36th International Conference on Software Engineering, ICSE 2014 ; Conference date: 31-05-2014 Through 07-06-2014",
}