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首页> 外文期刊>Theoretical computer science >On inter-deriving small-step and big-step semantics: A case study for storeless call-by-need evaluation
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On inter-deriving small-step and big-step semantics: A case study for storeless call-by-need evaluation

机译:关于互导的小步和大步语义:无存储按需求值的案例研究

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Starting from the standard call-by-need reduction for the λ-calculus that is common to Ariola, Felleisen, Maraist, Odersky, and Wadler, we inter-derive a series of hygienic semantic artifacts: a reduction-free storeless abstract machine, a continuation-passing evaluation function, and what appears to be the first heapless natural semantics for call-by-need evaluation. Furthermore we observe that the evaluation function implementing this natural semantics is in defunctionalized form. The refunctionalized counterpart of this evaluation function implements an extended direct semantics in the sense of Cartwright and Felleisen. Overall, the semantic artifacts presented here are simpler than many other such artifacts that have been independently worked out, and which require ingenuity, skill, and independent soundness proofs on a case-by-case basis. They are also simpler to inter-derive because the inter-derivational tools (e.g., refocusing and defunctionalization) already exist.
机译:从Ariola,Felleisen,Maraist,Odersky和Wadler常见的λ演算的标准按需缩减开始,我们推论出一系列卫生的语义工件:无缩减的无存储抽象机器,连续传递评估功能,以及按需评估的第一个无堆自然语义。此外,我们观察到,实现这种自然语义的评估功能处于去功能化形式。经过重新功能化的此评估功能的对应物在Cartwright和Felleisen的意义上实现了扩展的直接语义。总体而言,这里介绍的语义工件比其他许多已经独立制定的工件要简单,并且需要逐案,独创,技能和独立的健全性证明。它们也更易于推导,因为已经存在推导工具(例如重新聚焦和去功能化)。

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