Publication | ACM Transactions on Modeling and Computer Simulation 2019

Extending Explicitly Modelled Simulation Debugging Environments with Dynamic Structure

Abstract

Extending Explicitly Modelled Simulation Debugging Environments with Dynamic Structure

Simon Van Mierlo, Hans Vangheluwe, Simon Breslav, Rhys Goldstein, Azam Khan

ACM Transactions on Modeling and Computer Simulation 2019

The widespread adoption of Modelling and Simulation (Mu0026S) techniques hinges on the availability of tools supporting each phase in the Mu0026S-based workflow. This includes tasks such as specifying, implementing, experimenting with, as well as debugging simulation models. We have previously developed a technique where advanced debugging environments are generated from an explicit behavioral model of the user interface and the simulator. These models are extracted from the code of existing modelling environments and simulators, and instrumented with debugging operations. This technique can be reused for a large family of modelling formalisms, but was not yet considered for dynamic-structure formalisms; debugging models in these formalisms is challenging, as entities can appear and disappear during simulation. In this paper, we adapt and apply our approach to accommodate dynamic-structure formalisms. To this end, we present a modular, reusable approach, which includes an architecture and a workflow. We observe that to effectively debug dynamic-structure models, domain-specific visualizations developed by the modeller should be (re)used for debugging tasks. To demonstrate our technique, we use Dynamic-Structure DEVS (DSDEVS) (a formalism that includes the characteristics of discrete-event and agent-based modelling paradigms) and an implementation of its simulation semantics in the PythonPDEVS tool as a running example. We apply our technique on NetLogo,a popular multi-agent simulation tool, to demonstrate the generality of our approach. Additional Key Words and Phrases: Debugging, Dynamic-Structure Formalisms, Visual Modelling and Experimentation Interfaces.

Download publication

Related Resources

Publication

2019

An Empirical Study of how Socio-Spatial Formations are influenced by Interior Elements and Displays in an Office Context

The design of a workplace can have a profound impact on the…

Publication

2020

SpaceAnalysis: A Tool for Pathfinding, Visibility, and Acoustics Analyses in Generative Design Workflows

A growing number of architectural design efforts are making use of…

Publication

2017

Simulation-Based Architectural Design

In recent decades, architects have turned to computer simulation with…

Publication

2022

Evolving Through the Looking Glass: Learning Improved Search Spaces with Variational Autoencoders.

Nature has spent billions of years perfecting our genetic…

Get in touch

Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.

Contact us