The use of agent-based systems is suitable for the construction of complex software. To guarantee a desirable social order one we must deal with the autonomy and diversity of interests of the agents and norms are efficient mechanisms of control used to regulate the behavior of the agents. Software testing still have been widely applied to ensure the software quality. In the context of normative multiagent systems, the test must deal with the need for the agents to act robustly under dynamic normative conditions in which the developers did not consider. In this context, we propose an approach to test normative agents that follow the belief-desire-intention model. Among the contributions, this thesis presents: a framework for development of normative BDI agents, the NBDI4JADE; a fault model to support the identification of different types of failures in normative agents; a framework for testing normative BDI agents, the N-JAT4BDI, and a method for generating test cases from ANA-ML models.We evaluated the test framework through an experimental study in which we discussed the efficiency and effectiveness of the framework. We also evaluate the effectiveness of the test case generation method, applying it to two usage scenarios: (i) a system to the manage submission and the review process of articles in conferences, and (ii) a system of sale of tour packages from a travel agency. The results obtained in the evaluations of both frameworks presented positive indications of efficiency and effectiveness in the detection and identification of failures in normative agents and efficiency in the generation of test cases.