Why Read This Chapter? To help you decide how to check your simulationboth against its antecedent conceptual models (verification) and external standards such as data (validation) -and in this way help you to establish the credibility of your simulation. In order to do this the chapter will point out the nature of these processes, including the variety of ways in which people seek to achieve them. Abstract Verification and validation are two important aspects of model building. Verification and validation compare models with observations and descriptions of the problem modelled, which may include other models that have been verified and validated to some level. However, the use of simulation for modelling social complexity is very diverse. Often, verification and validation do not refer to an explicit stage in the simulation development process, but to the modelling process itself, according to good practices and in a way that grants credibility to using the simulation for a specific purpose. One cannot consider verification and validation without considering the purpose of the simulation. This chapter deals with a comprehensive outline of methodological perspectives and practical uses of verification and validation. The problem of verification and validation is tackled in three main topics: (1) the meaning of the terms verification and validation in the context of simulating social complexity; (2) methods and techniques related to verification, including static and dynamic methods, good programming practices, defensive programming, and replication for model alignment; and (3) types and techniques of validation as well as their relationship to different modelling strategies.

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Verification and validation are two important aspects of model building. Verification and validation compare models with observations and descriptions of the problem modelled, which may include other models that have been verified and validated to some level. However, the use of simulation for modelling social complexity is very diverse. Often, verification and validation do not refer to an explicit stage in the simulation development process, but to the modelling process itself, according to good practices and in a way that grants credibility to using the simulation for a specific purpose. One cannot consider verification and validation without considering the purpose of the simulation. This chapter deals with a comprehensive outline of methodological perspectives and practical uses of verification and validation. The problem of evaluating simulations is addressed in four main topics: (1) the meaning of the terms verification and validation in the context of simulating social complexity; (2) types of validation, as well as techniques for validating simulations; (3) model replication and comparison as cornerstones of verification and validation; and (4) the relationship of various validation types and techniques with different modelling strategies. Why Read This Chapter? To help you decide how to check your simulation-both against its antecedent conceptual models (verification) and external standards such as data or other simulations (validation)-and in this way help you to establish the credibility of your simulation. In order to do this the chapter will point out the nature of these processes, including the variety of ways in which people seek to achieve them.

Abstract. The terms 'verification' and 'validation' are widely used in science, both in the natural and the social sciences. They are extensively used in simulation, often associated with the need to evaluate models in different stages of the simulation development process. Frequently, terminological ambiguities arise when researchers conflate, along the simulation development process, the technical meanings of both terms with other meanings found in the philosophy of science and the social sciences. This article considers the problem of verification and validation in social science simulation along five perspectives: The reasons to address terminological issues in simulation; the meaning of the terms in the philosophical sense of the problem of "truth"; the observation that some debates about these terms in simulation are inadvertently more terminological than epistemological; the meaning of the terms in the technical context of the simulation development process; and finally, a comprehensive outline of the relation between terminology used in simulation, different types of models used in the development process and different epistemological perspectives.