利用循环切割和制表机制提高全局SLS分辨率
Enhancing Global SLS-Resolution with Loop Cutting and Tabling Mechanisms
摘要：
全局SLS解析是一种众所周知的过程语义，用于在有根据的模型下自上而下计算查询。它继承了SLDNF-解析的{ \em linearity}属性，这使得使用简单的基于堆栈的存储器结构可以轻松有效地实现。然而，像SLDNF-分辨率，它遭受的无限循环和冗余计算的问题。为了解决这个问题，在本文中，我们开发了一个新的过程语义，称为{ \em SLTNF-resolution}，通过增强全局SLS-分辨率与循环切割和制表机制。SLTNF-分辨率是健全和完整的w.r.t.该方法为具有有界项大小性质的逻辑程序提供了良基语义，优于已有的线性制表过程语义，如SLT-解析.
英文摘要：
Global SLS-resolution is a well-known procedural semantics for top-down computation of queries under the well-founded model. It inherits from SLDNF-resolution the {\em linearity} property of derivations, which makes it easy and efficient to implement using a simple stack-based memory structure. However, like SLDNF-resolution it suffers from the problem of infinite loops and redundant computations. To resolve this problem, in this paper we develop a new procedural semantics, called {\em SLTNF-resolution}, by enhancing Global SLS-resolution with loop cutting and tabling mechanisms. SLTNF-resolution is sound and complete w.r.t. the well-founded semantics for logic programs with the bounded-term-size property, and is superior to existing linear tabling procedural semantics such as SLT-resolution.
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