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

JENSEN, Peter G., Kim G. LARSEN and Jiří SRBA. PTrie: Data Structure for Compressing and Storing Sets via Prefix Sharing. In Proceedings of the 14th International Colloquium on Theoretical Aspects of Computing (ICTAC'17). Holland: Springer, 2017, p. 248-265. ISBN 978-3-319-67728-6. Available from: https://dx.doi.org/10.1007/978-3-319-67729-3_15.

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

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: Netherlands
• Confidentiality degree: is not subject to a state or trade secret
• 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: 0302-9743
• Doi: http://dx.doi.org/10.1007/978-3-319-67729-3_15
• UT WoS: 000516829800015
• Keywords in English: data structure; set; prefix sharing; model checking
• Tags: firank_B

Abstract

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.