Adaptive concretization is a program synthesis technique that enables efficient parallelization of challenging synthesis problems. The key observation behind adaptive concretization is that in a challenging synthesis problem, there are some unknowns that are best suited for explicit search and some that are best suited for symbolic search through constraint solving. At a high level, the main id...

Program synthesis tools work by searching for an implementation that satisfies a given specification. Two popular search strategies are symbolic search, which reduces synthesis to a formula passed to a SAT solver, and explicit search, which uses brute force or random search to find a solution. In this paper, we propose adaptive concretization, a novel synthesis algorithm that combines the best ...

Abstract interpretation is a particularly well-suited methodology to build modular correctness proof of static analysers. Proof modularity becomes essential when correctness proof is machine checked for realistic languages To deal with complex concrete and abstract domains, the notion of parameterised concretization has been proposed to allow a structural decomposition of the abstract domain an...

Algorithm concretization with robots combines hands-on robotics and traditional algorithm visualization techniques to assist diverse learners to understand the basic idea of a given algorithm. In this way, we bring algorithms into the real physical world where students can touch the data structures during the execution. We present a proof-of-concept implementation with a few sorting algorithms....

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Traditional accounts of explanation fail to illuminate the explanatory relevance of “models that are descriptively false” in the sense that the regularities they entail fail to obtain. In this paper, I propose an account of explanation, which I call ‘explanation by concretization’, that serves to explicate the explanatory relevance of such models. Starting from a highly abstract and idealized m...

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The rapid proliferation of enormous sources of digital data and the development of cloud computing have led to greater dependence on data-intensive services. Each service may actually request or create a large amount of data sets. The scope, number, and complexity of data-intensive services are all set to soar in the future. To compose these services will be more challenging. Issues of autonomy...