Simulation model verification and validation

Robinson, Stewart

doi:10.1145/268437.268448

Cited by 136 publications

(87 citation statements)

References 8 publications

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“…Two key points sufficient accuracy, and built for a specific purpose have been identified for model validation. No model can be 100% accurate therefore model validation aims to access that a model is sufficiently accurate to achieve the purpose for which it is built (Robinson, 1997(Robinson, , 2014. Researchers have developed many methods for simulation model validation such as conceptual model validation, Black-box validation, Experimentation validation, white-box validation, and Solution validation.…”

Section: Proposed Model Validationmentioning

confidence: 99%

A scenario-based distributed testing model for software applications

Mehmood

Mahmood²,

Khan

et al. 2016

Int. j. adv. appl. sci

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Modern software applications are getting more complex in order to provide better service and quality. This complexity has given birth too many challenges for software testing such as functional discontinuation and detection of system level defects. Existing testing techniques which are based on test cases are time consuming and unable to offer higher confidence on quality of products for these complex applications. Distributed testing frameworks could be used to test complex software but these frameworks do not provide a global picture of testing activities and application status. This poor visibility results in poor control over testing activities. In this study we have proposed a distributed testing model (DisTest) using scenario-based testing technique. DisTest could be used with any COTS test automation tool and could be employed at any testing level. Result shows DisTest provides better visibility and control on testing activities and view of application status.

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Section: Proposed Model Validationmentioning

confidence: 99%

A scenario-based distributed testing model for software applications

Mehmood

Mahmood²,

Khan

et al. 2016

Int. j. adv. appl. sci

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“…The necessity of validating model elements at micro-and macro-levels in simulation studies was first recognized by Robinson (1997). He defined micro-check of the model as white-box validation and macro-check of the operation of the model as black-box validation.…”

Section: Levels Of Testingmentioning

confidence: 99%

“…As defined by Robinson (1997), data validation is needed to determine whether the data used are sufficently accurate. Windrum et al (2007) examine a set of methodological problems in the emprical validation of agent-based economics models.…”

Section: Related Workmentioning

confidence: 99%

A generic testing framework for agent-based simulation models

Gürcan

Dikenelli

Bernon³

2013

Journal of Simulation

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. Agent-based modelling and simulation (ABMS) had an increasing attention during the last decade. However, the weak validation and verification of agent-based simulation models makes ABMS hard to trust. There is no comprehensive tool set for verification and validation of agent-based simulation models, which demonstrates that inaccuracies exist and/or reveals the existing errors in the model. Moreover, on the practical side, many ABMS frameworks are in use. In this sense, we designed and developed a generic testing framework for agent-based simulation models to conduct validation and verification of models. This paper presents our testing framework in detail and demonstrates its effectiveness by showing its applicability on a realistic agent-based simulation case study.

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“…Both process models and process simulations have been undergone a vigorous validation process leading to the approvals from end users and supply chain engineers. In addition, other standard validation approaches were also deployed, such as those suggested by (Robinson and Bhatia 1995;Robinson 1997;Robinson 2006;Monfared, West et al 2007). The NGCCAS approach continues by designing a new business and engineering processes and supply chain interactions.…”

Section: Evaluation Of Impacts On Engineering Processesmentioning

confidence: 99%