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Award ID contains: 2006407

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  1. Nadel, Alexander; Rozier, Kristin Yvonne (Ed.)
    Syntax-guided synthesis (SyGuS) is a recent software synthesis paradigm in which an automated synthesis tool is asked to synthesize a term that satisfies both a semantic and a syntactic specification. We consider a special case of the SyGuS problem, where a term is already known to satisfy the semantic specification but may not satisfy the syntactic one. The goal is then to find an equivalent term that additionally satisfies the syntactic specification, provided by a context-free grammar. We introduce a novel procedure for solving this problem which leverages pattern matching and automated discovery of rewrite rules. We also provide an implementation of the procedure by modifying the SyGuS solver embedded in the cvc5 SMT solver. Our evaluation shows that our new procedure significantly outperforms the state of the art on a large set of SyGuS problems for standard SMT-LIB theories such as bit-vectors, arithmetic, and strings. 
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  2. Piskac, Ruzica; Whalen, Michael W. (Ed.)
    The increasing complexity of modern configurable systems makes it critical to improve the level of automation in the process of system configuration. Such automation can also improve the agility of the development cycle, allowing for rapid and automated integration of decoupled workflows. In this paper, we present a new framework for automated configuration of systems representable as state machines. The framework leverages model checking and satisfiability modulo theories (SMT) and can be applied to any application domain representable using SMT formulas. Our approach can also be applied modularly, improving its scalability. Furthermore, we show how optimization can be used to produce configurations that are best according to some metric and also more likely to be understandable to humans. We showcase this framework and its flexibility by using it to configure a CGRA memory tile for various image processing applications. 
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  3. null (Ed.)