D 2017

PTrie: Data Structure for Compressing and Storing Sets via Prefix Sharing

JENSEN, Peter G., Kim G. LARSEN and Jiří SRBA

Basic information

Original name

PTrie: Data Structure for Compressing and Storing Sets via Prefix Sharing

Authors

JENSEN, Peter G. (208 Denmark), Kim G. LARSEN (208 Denmark) and Jiří SRBA (203 Czech Republic, guarantor, belonging to the institution)

Edition

Holland, Proceedings of the 14th International Colloquium on Theoretical Aspects of Computing (ICTAC'17), p. 248-265, 18 pp. 2017

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10200 1.2 Computer and information sciences

Country of publisher

Netherlands

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14330/17:00100449

Organization unit

Faculty of Informatics

ISBN

978-3-319-67728-6

ISSN

UT WoS

000516829800015

Keywords in English

data structure; set; prefix sharing; model checking
Změněno: 16/5/2022 14:38, Mgr. Michal Petr

Abstract

V originále

Sets and their efficient implementation are fundamental in all of computer science, including model checking, where sets are used as the basic data structure for storing (encodings of) states during a state-space exploration. In the quest for fast and memory efficient methods for manipulating large sets, we present a novel data structure called PTrie for storing sets of binary strings of arbitrary length. The PTrie data structure distinguishes itself by compressing the stored elements while sharing the desirable key characteristics with conventional hash-based implementations, namely fast insertion and lookup operations. We provide the theoretical foundation of PTries, prove the correctness of their operations and conduct empirical studies analysing the performance of PTries for dealing with randomly generated binary strings as well as for state-space exploration of a large collection of Petri net models from the 2016 edition of the Model Checking Contest (MCC'16). We experimentally document that with a modest overhead in running time, a truly significant space-reduction can be achieved. Lastly, we provide an efficient implementation of the PTrie data structure under the GPL version 3 license, so that the technology is made available for memory-intensive applications such as model-checking tools.