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For many mission critical systems, demonstrating that all requirements have been met via a set of requirements-based tests is often mandated by internal processes or external standards. Traditional coverage approaches, however, do not address this mandate because they measure only the coverage of the design by determining which paths in the design have been executed. Determining whether a given set of test vectors covers the design requirements (as opposed to merely covering the design) is a challenge. Creating a set of test vectors to cover the requirements can be difficult and time consuming. Using techniques first identified in the 1970s and modern Model-Based Design tools, we present a novel approach, based on work presented in [2], to automatically generate a set of requirements-based test vectors. In this paper, we discuss how requirements captured in a natural language can be modeled using Cause-Effect graphs, introduced in [1].

The transition to Model-Based Design must be managed carefully, both to demonstrate short-term benefits and to establish a culture that enables the full realization of the theoretical benefits of this approach. In this paper we introduce the concepts of Model-Based Design, highlight some of its benefits, and then discuss in detail the 10 best practices for adopting a Model-Based Design culture across an organization. These best practices have been gleaned from successful and not-so-successful transformations to Model-Based Design at companies from a variety of different industries.