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A Coverage Metric to Aid in Testing Multi-Agent SystemsLinn, Jane Ostergar 01 December 2017 (has links)
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.
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Metamodeling Driven IP Reuse for System-on-chip Integration and Microprocessor DesignMathaikutty, Deepak Abraham 02 December 2007 (has links)
This dissertation addresses two important problems in reusing intellectual properties (IPs) in the form of reusable design or verification components. The first problem is associated with fast and effective integration of reusable design components into a System-on-chip (SoC), so faster design turn-around time can be achieved, leading to faster time-to-market. The second problem has the same goals of faster product design cycle, but emphasizes on verification model reuse, rather than design component reuse. It specifically addresses reuse of reusable verification IPs to enable a "write once, use many times" verification strategy. This dissertation is accordingly divided into part I and part II which are related but describe the two problems and our solutions to them.
These two related but distinctive problems faced by system design companies have been tackled through a unique approach which hither-to-fore only have been used in the software engineering domain. This approach is called metamodeling, which allows creating customized meta-language to describe the syntax and semantics for a modeling domain. It provides a way to create, transform and analyze domain specific languages, which are themselves described by metamodels, and the transformation and processing of models in such languages are also described by metamodels. This makes machine based interpretation and translation from these models an easier and formal task.
In part I, we consider the problem of rapid system-level model integration of existing reusable components such that (i) the required architecture of the SoC can be expressed formally, (ii) automatic selection of components from an IP library to match the need of the system being integrated can be done, (iii) integrability of the components is provable, or checkable automatically, and (iv) structural and behavioral type systems for each component can be utilized through inferencing and matching techniques to ensure their compatibility. Our solutions include a component composition language, algorithms for component selection, type matching and inferencing algorithms, temporal property based behavioral typing, and finally a software system on top of an existing metamodeling environment.
In part II, we use the same metamodeling environment to create a framework for modeling generative verification IPs. Our main contributions relate to INTEL's microprocessor verification environment, and our solution spans various abstraction levels (System, architectural, and microarchitecture) to perform verification. We provide a unified language that can be used to model verification IPs at all abstraction levels, and verification collaterals such as testbenches, simulators, and coverage monitors can be generated from these models, thereby enhancing reuse in verification. / Ph. D.
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