Abstract

Models are frequently used to represent complex systems in order to test the systems before they are deployed. Some of the most complicated models are those that represent multi-agent systems (MAS), where there are multiple decision makers. Brahms is an agent-oriented language that models MAS. Three major qualities affect the behavior of these MAS models: workframes that change the state of the system, communication activities that coordinate information between agents, and the schedule of workframes. The primary method to test these models that exists is repeated simulation. Simulation is useful insofar as interesting test cases are used that enable the simulation to explore different behaviors of the model, but simulation alone cannot be fully relied upon to adequately cover the test space, especially in the case of non-deterministic concurrent systems. It takes an exponential number of simulation trials to uncover schedules that reveal unexpected behaviors. This thesis defines a coverage metric to make simulation more meaningful before verification of the model. The coverage metric is divided into three different metrics: workframe coverage, communication coverage, and schedule coverage. Each coverage metric is defined through static analysis of the system, resulting in the coverage requirements of that system. These coverage requirements are compared to the logged output of the simulation run to calculate the coverage of the system. The use of the coverage metric is illustrated in several empirical studies and explored in a detailed case study of the SATS concept (Small Aircraft Transportation System). SATS outlines the procedures aircraft follow around runways that do not have communication towers. The coverage metric quantifies the test effort, and can be used as a basis for future automated test generation and active test.

Degree

College and Department

Physical and Mathematical Sciences; Computer Science

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