Multi-agent systems (MASs) are distributed and complex software that demand specific software engineering features. Testing is a critical phase when validating software, and it is also difficult to conceive and execute. Designing systems under a multi-agent paradigm is even more difficult because of properties such as autonomy, reactivity, pro-activity, and social skills. Any multi-agent system has at least three main dimensions: the individual and social levels and communication interfaces. Considering an approach for testing a dimension specifically, we deal with the social level as an organizational model in this paper. It imposes some restrictions on agents’ behavior through a set of behavioral constraints. In this sense, an error in the organization can occur when the allocated resources are not enough for executing plans and reaching goals. This work aims to present a whole framework for analyzing and testing MAS social level under organizational model Moise+. This framework uses a Moise+ specifications set as information artifact mapped in a colored Petri net (CPN) model, named CPN4M, as a test case generation mechanism. CPN4M uses two different test adequacy criteria: all-paths and state-transition path. In this paper, we have formalized the transition from Moise+ to CPN, the procedures for test case generation, and executed some tests in a case study. The results indicate that this methodology can increase the correction degree for a social level in a multi-agent system specified by a Moise+ model, indicating the system context that can lead the MAS for failures.
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