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While the topic of validating simulation models is rich in literature, validating the environments in which models run has been poorly researched. Despite the fact that such environments have high face validity, in most of the cases there are no formal methods developed for validating them. In this project, we first distinguish between the different forms of validity, such as data, model, and environment validity and then we propose an automated procedure for validating simulation environments, similar to what unit testing is for verification.doi:10.1109/wsc.2016.7822395 dblp:conf/wsc/Roungas16 fatcat:schdxbel3bfq7kvqmvuak3undm