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In software development, formal verification plays an important role in improving the quality and safety of products and processes. Model checking is a successful approach to verification, used both in academic research and industrial applications. One important improvement regarding utilization of model checking is the development of automated processes to evolve models according to information obtained from verification. In this paper, we propose a new framework that make use of artificial intelligence and machine learning to generate and evolve models from partial descriptions and examples created by the model checking process. This was implemented as a tool that is integrated with a model checker. Our work extends model checking to be applicable when initial description of a system is not available, through observation of actual behaviour of this system. The framework is capable of integrated verification and evolution of abstract models, but also of reengineering partial models of a system.

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The development of analogical reasoning has traditionally been understood in terms of theories of adult competence. This approach emphasizes structured representations and structure mapping. In contrast, we argue that by taking a developmental perspective, analogical reasoning can be viewed as the product of a substantially different cognitive ability -relational priming. To illustrate this, we present a computational (here connectionist) account where analogy arises gradually as a by-product of pattern completion in a recurrent network. Initial exposure to a situation primes a relation that can then be applied to a novel situation to make an analogy. Relations are represented as transformations between states. The network exhibits behaviors consistent with a broad range of key phenomena from the developmental literature, lending support to the appropriateness of this approach (using low-level cognitive mechanisms) for investigating a domain that has normally been the preserve of high-level models. Furthermore, we present an additional simulation that integrates the relational priming mechanism with deliberative controlled use of inhibition to demonstrate how the framework can be extended to complex analogical reasoning, such as the data from explicit mapping studies in the literature on adults. This account highlights how taking a developmental perspective constrains the theory construction and cognitive modeling processes in a way that differs substantially from that based purely on adult studies, and illustrates how a putative complex cognitive skill can emerge out of a simple mechanism.

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