3,276 research outputs found

    Succinct Indexable Dictionaries with Applications to Encoding kk-ary Trees, Prefix Sums and Multisets

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    We consider the {\it indexable dictionary} problem, which consists of storing a set S{0,...,m1}S \subseteq \{0,...,m-1\} for some integer mm, while supporting the operations of \Rank(x), which returns the number of elements in SS that are less than xx if xSx \in S, and -1 otherwise; and \Select(i) which returns the ii-th smallest element in SS. We give a data structure that supports both operations in O(1) time on the RAM model and requires B(n,m)+o(n)+O(lglgm){\cal B}(n,m) + o(n) + O(\lg \lg m) bits to store a set of size nn, where {\cal B}(n,m) = \ceil{\lg {m \choose n}} is the minimum number of bits required to store any nn-element subset from a universe of size mm. Previous dictionaries taking this space only supported (yes/no) membership queries in O(1) time. In the cell probe model we can remove the O(lglgm)O(\lg \lg m) additive term in the space bound, answering a question raised by Fich and Miltersen, and Pagh. We present extensions and applications of our indexable dictionary data structure, including: An information-theoretically optimal representation of a kk-ary cardinal tree that supports standard operations in constant time, A representation of a multiset of size nn from {0,...,m1}\{0,...,m-1\} in B(n,m+n)+o(n){\cal B}(n,m+n) + o(n) bits that supports (appropriate generalizations of) \Rank and \Select operations in constant time, and A representation of a sequence of nn non-negative integers summing up to mm in B(n,m+n)+o(n){\cal B}(n,m+n) + o(n) bits that supports prefix sum queries in constant time.Comment: Final version of SODA 2002 paper; supersedes Leicester Tech report 2002/1

    08081 Abstracts Collection -- Data Structures

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    From February 17th to 22nd 2008, the Dagstuhl Seminar 08081 ``Data Structures\u27\u27 was held in the International Conference and Research Center (IBFI), Schloss Dagstuhl. It brought together 49 researchers from four continents to discuss recent developments concerning data structures in terms of research but also in terms of new technologies that impact how data can be stored, updated, and retrieved. During the seminar a fair number of participants presented their current research. There was discussion of ongoing work, and in addition an open problem session was held. This paper first describes the seminar topics and goals in general, then gives the minutes of the open problem session, and concludes with abstracts of the presentations given during the seminar. Where appropriate and available, links to extended abstracts or full papers are provided

    Proving Tree Algorithms for Succinct Data Structures

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    Succinct data structures give space-efficient representations of large amounts of data without sacrificing performance. They rely on 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
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