Before revision:  Model replication is a possible solution to this problem, as it bypasses the biases associated with the language or toolkit used to develop the original model, promoting model verification , model validation, and improved modelunderstanding. Some argue that a computational model is untrustworthy until it has been successfully replicated. However, most models have only been implemented by the original developer, and thus, have never been replicated. Several reasons for this problem have been identified, namely: a) lack of incentive; b) below par modelcommunication; c) insufficient knowledge of how to replicate; and, d) level of difficulty of the replication task.
After revision:  Model replication is a possible solution to this problem, as it bypasses the biases associated with the language or toolkit used to develop the original model, not only promoting its verification and validation, but also fostering the credibility of the underlying conceptual model. However, different model implementations must be compared to assess their equivalence. The problem is, given two or more implementations of a stochastic model, how to prove that they display similar behavior?