## 4 Testing \(\mathcal{M}\text{oise}^{+}\) Using Different Test Adequacy Criterion  
This section will present a method for testing MASs under the \(\mathcal{M}\text{oise}^{+}\) organizational model. The method uses its three specification types (FS, SS, and DS) as information artifact, a CPN model as the generation mechanism for the test case generation, and a test suite with two coverage criteria: _all paths_ and _state transition path_. In the _all paths_ criteria, the number of execution paths mapped inside a CPN is calculated and used as the reference to assess its testability. The second criteria, called _state transition path_, is based on the sum of the paths in the CPN state spaces, i.e., its reachability graph. We offer a test approach based on a perspective in which an MAS is seen from three dimensions in a global view of its development [23]: (i) an _organization_, corresponding to the social level, in which the elements that allow for agent interaction and coordination between agents are formally or informally structured; (ii) the _communication_ level concerned with issues such as protocols and information exchanges between agents; and, finally, (iii) the _agents_ level relates to the individual level specification, where the organization's requests are instantiated based on each agent's individual capacities and skills. In this context, this article focuses on tests related to the organization of a multi-agent system in this context. Recovering the context presented in the Introduction, in an MAS, an organization is a set of roles, relationships, and authority structures that regulate behaviors. Even if it exists just implicitly and informally or through formal organizational models, the organization exists. These rules have an impact on data flow, resource allocation, coordination standards, authority relationships, and other aspects of the system [40]. \(\mathcal{M}\text{oise}^{+}\) is one of the most referenced organizational models. It considers an MAS to be an organization or a set of normative rules that limit the agent's actions. Three fundamental concepts represent these organizational restrictions: roles, plans, and norms [31]. It has three levels of structure (individual, collective, and social) and three forms of specification (structural, functional, and deontic). Each agent's available behaviors are constrained at the individual level. The number of agents who can cooperate is limited at the collective level. Finally, the social level limits the kind of interactions that the agents can perform. The following are the reasons for using Petri nets to map an MAS [41]: (i) they give a graphical and mathematically based modeling framework, which is a must for system development procedures that require both graphical and algorithmic tools; (ii) as a result of the \(\mathcal{M}\text{oise}^{+}\) specification's abstraction and hierarchical refinement processes, they can incorporate the different levels and types of the specification; (iii) there are numerous algorithms for the creation and analysis of Petri nets, as well as powerful tools to assist in these processes; (iv) Petri net models come in a variety of models, but they are all linked by the basic formalism on which they are based. Furthermore, extensions such as timed,stochastic, high-level, and others, and the base model, the ordinary Petri net, fulfill the unique needs of practically every application field. However, once several dimensions of representation, defined by a structural specification (SS), a functional specification (FS), and a deontic specification (DS), are integrated, the standard Petri net model is insufficient to represent a comprehensive \(\mathcal{M}\text{oise}^{+}\) model [31]. Therefore, our approach contains a mapping procedure that uses a model based on colored Petri nets [19] since it requires a more powerful representation resource. In our method, colored tokens are labels used to represent the organization's roles and groups.