Validation of System-level Properties at Code Level

Author(s):  
Pierre-Loïc Garoche

This chapter claims that code generation can be adapted to enable the expression of system-level properties at code level, and be later proved with respect to the code semantics. All previous analyses were performed on discrete dynamical systems models. However, once the control-level properties have been expressed and analyzed at model level, their validity must be asserted on the code artifact extracted from the model. Luckily, this extraction of code from models is largely automatized thanks to autocoding framework generating embedded code from dataflow models. Indeed, code generation from dataflow language is now effective and widely used in the industry. With these in mind, the chapter first gives an overview of the modeling framework, enabling the expression of properties at model and code level. A second part explains the generation of such code annotations, while a last part focuses on their verification.

NeuroImage ◽  
2011 ◽  
Vol 54 (2) ◽  
pp. 807-823 ◽  
Author(s):  
Srikanth Ryali ◽  
Kaustubh Supekar ◽  
Tianwen Chen ◽  
Vinod Menon

2017 ◽  
Author(s):  
Wayne M. Getz ◽  
Richard Salter ◽  
Oliver Muellerklein ◽  
Hyun S. Yoon ◽  
Krti Tallam

AbstractEpidemiological models are dominated by SEIR (Susceptible, Exposed, Infected and Removed) dynamical systems formulations and their elaborations. These formulations can be continuous or discrete, deterministic or stochastic, or spatially homogeneous or heterogeneous, the latter often embracing a network formulation. Here we review the continuous and discrete deterministic and discrete stochastic formulations of the SEIR dynamical systems models, and we outline how they can be easily and rapidly constructed using the Numerus Model Builder, a graphically-driven coding platform. We also demonstrate how to extend these models to a metapopulation setting using both the Numerus Model Builder network and geographical mapping tools.


2001 ◽  
Vol 24 (1) ◽  
pp. 50-51 ◽  
Author(s):  
Arthur B. Markman

The proposed model is put forward as a template for the dynamical systems approach to embodied cognition. In order to extend this view to cognitive processing in general, however, two limitations must be overcome. First, it must be demonstrated that sensorimotor coordination of the type evident in the A-not-B error is typical of other aspects of cognition. Second, the explanatory utility of dynamical systems models must be clarified.


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