Proving tree algorithms for succinct data structures

Reynald Affeldt, Jacques Garrigue, Xuanrui Qi, Kazunari Tanaka
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引用次数: 2

Abstract

Succinct data structures give space-efficient representations of large amounts of data without sacrificing performance. They rely one cleverly designed data representations and algorithms. We present here the formalization in Coq/SSReflect of two different tree-based succinct representations and their accompanying algorithms. One is the Level-Order Unary Degree Sequence, which encodes the structure of a tree in breadth-first order as a sequence of bits, where access operations can be defined in terms of Rank and Select, which work in constant time for static bit sequences. The other represents dynamic bit sequences as binary balanced trees, where Rank and Select present a low logarithmic overhead compared to their static versions, and with efficient insertion and deletion. The two can be stacked to provide a dynamic representation of dictionaries for instance. While both representations are well-known, we believe this to be their first formalization and a needed step towards provably-safe implementations of big data.
证明树算法用于简洁的数据结构
简洁的数据结构在不牺牲性能的情况下为大量数据提供了节省空间的表示。它们依赖于一种巧妙设计的数据表示和算法。本文介绍了Coq/SSReflect中两种不同的基于树的简洁表示及其相应的算法的形式化。一种是Level-Order Unary Degree Sequence,它以宽度优先顺序将树的结构编码为位序列,其中访问操作可以根据Rank和Select定义,对于静态位序列,它们在恒定时间内工作。另一种将动态位序列表示为二叉平衡树,其中Rank和Select与静态版本相比具有较低的对数开销,并且具有高效的插入和删除。可以将两者叠加以提供例如字典的动态表示。虽然这两种表示都是众所周知的,但我们认为这是它们的第一次形式化,也是迈向可证明安全的大数据实现的必要步骤。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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