survey

Predecessor Search

Authors:

Gonzalo Navarro,

Javiel Rojas-LedesmaAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 53, Issue 5

Article No.: 105, Pages 1 - 35

https://doi.org/10.1145/3409371

Published: 28 September 2020 Publication History

Abstract

The predecessor problem is a key component of the fundamental sorting-and-searching core of algorithmic problems. While binary search is the optimal solution in the comparison model, more realistic machine models on integer sets open the door to a rich universe of data structures, algorithms, and lower bounds. In this article, we review the evolution of the solutions to the predecessor problem, focusing on the important algorithmic ideas, from the famous data structure of van Emde Boas to the optimal results of Patrascu and Thorup. We also consider lower bounds, variants, and special cases, as well as the remaining open questions.

Supplementary Material

a105-navarro-apndx.pdf (navarro.zip)

Supplemental movie, appendix, image and software files for, Predecessor Search

Download
50.47 KB

References

[1]

Peyman Afshani, Cheng Sheng, Yufei Tao, and Bryan T. Wilkinson. 2014. Concurrent range reporting in two-dimensional space. In Proceedings of the 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’14), Chandra Chekuri (Ed.). SIAM, 983--994.

[2]

Alok Aggarwal and Jeffrey Scott Vitter. 1988. The input/output complexity of sorting and related problems. Commun. ACM 31, 9 (1988), 1116--1127.

Digital Library

[3]

Alfred V. Aho, John E. Hopcroft, and Jeffrey D. Ullman. 1976. On finding lowest common ancestors in trees. SIAM J. Comput. 5, 1 (1976), 115--132.

Digital Library

[4]

Miklós Ajtai. 1988. A lower bound for finding predecessors in Yao’s cell probe model. Combinatorica 8, 3 (1988), 235--247.

[5]

Miklós Ajtai, Michael L. Fredman, and János Komlós. 1984. Hash functions for priority queues. Info. Control 63, 3 (1984), 217--225.

Digital Library

[6]

Stephen Alstrup, Gerth Stølting Brodal, and Theis Rauhe. 2001. Optimal static range reporting in one dimension. In Proceedings of the 33rd Annual ACM Symposium on Theory of Computing (STOC’01). 476--482.

Digital Library

[7]

Stephen Alstrup, Thore Husfeldt, and Theis Rauhe. 1998. Marked ancestor problems. In Proceedings of the 39th Annual Symposium on Foundations of Computer Science (FOCS’98). 534--544.

[8]

Arne Andersson. 1995. Sublogarithmic searching without multiplications. In Proceedings of the 36th Annual Symposium on Foundations of Computer Science (FOCS’95). 655--663.

Digital Library

[9]

Arne Andersson. 1996. Faster deterministic sorting and searching in linear space. In Proceedings of the 37th Annual Symposium on Foundations of Computer Science (FOCS’96). 135--141.

Digital Library

[10]

Arne Andersson, Torben Hagerup, Stefan Nilsson, and Rajeev Raman. 1998. Sorting in linear time? J. Comput. Syst. Sci. 57, 1 (1998), 74--93.

Digital Library

[11]

Arne Andersson and Christer Mattsson. 1993. Dynamic interpolation search in o(log log n) time. In Proceedings of the 20th International Colloquium on Automata, Languages and Programming (ICALP’93). 15--27.

Digital Library

[12]

Arne Andersson and Mikkel Thorup. 2007. Dynamic ordered sets with exponential search trees. Journal of the ACM 54, 3 (2007), 13.

Digital Library

[13]

Lars Arge, Paolo Ferragina, Roberto Grossi, and Jeffrey Scott Vitter. 1997. On sorting strings in external memory. In Proceedings of the 29th Annual ACM Symposium on the Theory of Computing (STOC’97), Frank Thomson Leighton and Peter W. Shor (Eds.). ACM, 540--548.

[14]

Paul Beame and Faith E. Fich. 2002. Optimal bounds for the predecessor problem and related problems. J. Comput. Syst. Sci. 65, 1 (2002), 38--72.

Digital Library

[15]

Djamal Belazzougui. 2012. Worst-case efficient single and multiple string matching on packed texts in the word-RAM model. J. Discrete Algor. 14 (2012), 91--106.

Digital Library

[16]

Djamal Belazzougui. 2016. Predecessor search, string algorithms and data structures. In Encyclopedia of Algorithms. 1605--1611.

[17]

Djamal Belazzougui, Paolo Boldi, Rasmus Pagh, and Sebastiano Vigna. 2009. Monotone minimal perfect hashing: Searching a sorted table with O(1) accesses. In Proceedings of the 20th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’09). 785--794.

Digital Library

[18]

Djamal Belazzougui, Paolo Boldi, Rasmus Pagh, and Sebastiano Vigna. 2010. Fast prefix search in little space, with applications. In Proceedings of the 18th Annual European Symposium on Algorithms (ESA’10). 427--438.

[19]

Djamal Belazzougui, Paolo Boldi, and Sebastiano Vigna. 2010. Dynamic z-fast tries. In Proceedings of the 17th International Symposium on String Processing and Information Retrieval (SPIRE’10). 159--172.

[20]

Djamal Belazzougui, Paolo Boldi, and Sebastiano Vigna. 2012. Predecessor search with distance-sensitive query time. CoRR abs/1209.5441.

[21]

Djamal Belazzougui, Alexis C. Kaporis, and Paul G. Spirakis. 2018. Random input helps searching predecessors. In Proceedings of the 11th International Conference on Random and Exhaustive Generation of Combinatorial Structures (GASCom’18). 106--115.

[22]

Djamal Belazzougui and Gonzalo Navarro. 2015. Optimal lower and upper bounds for representing sequences. ACM Trans. Algor. 11, 4 (2015), 31:1--31:21.

[23]

Michael A. Bender, Martin Farach-Colton, Mayank Goswami, Dzejla Medjedovic, Pablo Montes, and Meng-Tsung Tsai. 2014. The batched predecessor problem in external memory. In Proceedings of the 22th Annual European Symposium on Algorithms (ESA’14). 112--124.

[24]

Michael A. Bender, Martin Farach-Colton, and Bradley C. Kuszmaul. 2006. Cache-oblivious string B-trees. In Proceedings of the 25th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems (PODS’06), Stijn Vansummeren (Ed.). ACM, 233--242.

[25]

Michael A. Bender, Mayank Goswami, Dzejla Medjedovic, Pablo Montes, and Kostas Tsichlas. 2020. Batched predecessor and sorting with size-priced information in external memory. CoRR abs/2004.13197. arxiv:2004.13197.

[26]

Samuel W. Bent, Daniel Dominic Sleator, and Robert Endre Tarjan. 1985. Biased search trees. SIAM J. Comput. 14, 3 (1985), 545--568.

[27]

Philip Bille, Mikko Berggren Ettienne, Inge Li Gørtz, and Hjalte Wedel Vildhøj. 2017. Time-space trade-offs for Lempel-Ziv compressed indexing. In Proceedings of the 28th Annual Symposium on Combinatorial Pattern Matching (CPM’17). 16:1--16:17.

[28]

Philip Bille, Pawel Gawrychowski, Inge Li Gørtz, Gad M. Landau, and Oren Weimann. 2016. Longest common extensions in trees. Theor. Comput. Sci. 638 (2016), 98--107.

Digital Library

[29]

Philip Bille, Inge Li Gørtz, and Frederik Rye Skjoldjensen. 2017. Deterministic indexing for packed strings. In Proceedings of the 28th Annual Symposium on Combinatorial Pattern Matching (CPM’17). 6:1--6:11.

[30]

Philip Bille, Gad M. Landau, Rajeev Raman, Kunihiko Sadakane, Srinivasa Rao Satti, and Oren Weimann. 2015. Random access to grammar-compressed strings and trees. SIAM J. Comput. 44, 3 (2015), 513--539.

Digital Library

[31]

Prosenjit Bose, Karim Douïeb, Vida Dujmovic, John Howat, and Pat Morin. 2013. Fast local searches and updates in bounded universes. Comput. Geom. 46, 2 (2013), 181--189.

Digital Library

[32]

Prosenjit Bose, Rolf Fagerberg, John Howat, and Pat Morin. 2016. Biased predecessor search. Algorithmica 76, 4 (2016), 1097--1105.

Digital Library

[33]

Gerth Stølting Brodal. 1997. Predecessor queries in dynamic integer sets. In Proceedings of the 14th Annual Symposium on Theoretical Aspects of Computer Science (STACS’97). 21--32.

[34]

Amit Chakrabarti and Oded Regev. 2004. An optimal randomised cell probe lower bound for approximate nearest neighbour searching. In Proceedings of the 45th Symposium on Foundations of Computer Science (FOCS’04). 473--482.

Digital Library

[35]

Timothy M. Chan. 2013. Persistent predecessor search and orthogonal point location on the word RAM. ACM Trans. Algorithms 9, 3 (2013), 22:1--22:22.

Digital Library

[36]

Timothy M. Chan, Kasper Green Larsen, and Mihai Patrascu. 2011. Orthogonal range searching on the RAM, revisited. In Proceedings of the 27th ACM Symposium on Computational Geometry (SoCG’11). 1--10.

Digital Library

[37]

Timothy M. Chan, Yakov Nekrich, Saladi Rahul, and Konstantinos Tsakalidis. 2018. Orthogonal point location and rectangle stabbing queries in 3D. In Proceedings of the 45th International Colloquium on Automata, Languages, and Programming (ICALP’18). 31:1--31:14.

[38]

Timothy M. Chan and Mihai Patrascu. 2009. Transdichotomous results in computational geometry, I: Point location in sublogarithmic time. SIAM J. Comput. 39, 2 (2009), 703--729.

Digital Library

[39]

Timothy M. Chan and Konstantinos Tsakalidis. 2017. Dynamic orthogonal range searching on the RAM, revisited. In Proceedings of the 33rd International Symposium on Computational Geometry (SoCG’17). 28:1--28:13.

[40]

Bernard Chazelle and Leonidas J. Guibas. 1986. Fractional cascading: I. A data structuring technique. Algorithmica 1, 2 (1986), 133--162.

Digital Library

[41]

David R. Clark. 1996. Compact PAT Trees. Ph.D. Dissertation. University of Waterloo, Canada.

Digital Library

[42]

Sarel Cohen, Amos Fiat, Moshik Hershcovitch, and Haim Kaplan. 2015. Minimal indices for predecessor search. Info. Comput. 240 (2015), 12--30.

Digital Library

[43]

Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein. 2009. Introduction to Algorithms (3rd ed.). MIT Press.

Digital Library

[44]

Roman Dementiev, Lutz Kettner, Jens Mehnert, and Peter Sanders. 2004. Engineering a sorted list data structure for 32 bit key. In Proceedings of the 6th Workshop on Algorithm Engineering and Experiments (ALENEX’04). 142--151.

[45]

Marcel Ehrhardt and Wolfgang Mulzer. 2017. Delta-fast tries: Local searches in bounded universes with linear space. In Proceedings of the 15th International Symposium on Algorithms and Data Structures (WADS’17). 361--372.

[46]

Peter Elias. 1974. Efficient storage and retrieval by content and address of static files. J. ACM 21, 2 (1974), 246--260.

Digital Library

[47]

Robert Mario Fano. 1971. On the Number of Bits Required to Implement an Associative Memory. Massachusetts Institute of Technology, Project MAC.

[48]

Martin Farach. 1997. Optimal suffix tree construction with large alphabets. In Proceedings of the 38th Symposium on Foundations of Computer Science (FOCS’97). IEEE Computer Society, 137--143.

[49]

Johannes Fischer and Pawel Gawrychowski. 2015. Alphabet-dependent string searching with wexponential search trees. In Proceedings of the 26th Annual Symposium on Combinatorial Pattern Matching (CPM’15). 160--171.

[50]

M. L. Fredman, J. Komlós, and E. Szemerédi. 1984. Storing a sparse table with O(1) worst case access time. J. ACM 31, 3 (1984), 538--544.

Digital Library

[51]

Michael L. Fredman and Dan E. Willard. 1993. Surpassing the information theoretic bound with fusion trees. J. Comput. Syst. Sci. 47, 3 (1993), 424--436.

Digital Library

[52]

Michael L. Fredman and Dan E. Willard. 1994. Trans-dichotomous algorithms for minimum spanning trees and shortest paths. J. Comput. Syst. Sci. 48, 3 (1994), 533--551.

Digital Library

[53]

Anna Gál and Peter Bro Miltersen. 2007. The cell probe complexity of succinct data structures. Theor. Comput. Sci. 379, 3 (2007), 405--417.

Digital Library

[54]

Roberto Grossi, Alessio Orlandi, Rajeev Raman, and S. Srinivasa Rao. 2009. More haste, less waste: Lowering the redundancy in fully indexable dictionaries. In Proceedings of the 26th International Symposium on Theoretical Aspects of Computer Science (STACS’09). 517--528.

[55]

Torben Hagerup. 1998. Sorting and searching on the word RAM. In Proceedings of the 15th Annual Symposium on Theoretical Aspects of Computer Science (STACS’98). 366--398.

Digital Library

[56]

Yijie Han. 2001. Improved fast integer sorting in linear space. Info. Comput. 170, 1 (2001), 81--94.

Digital Library

[57]

Yijie Han. 2004. Deterministic sorting in O(n log log n) time and linear space. J. Algor. 50, 1 (2004), 96--105.

Digital Library

[58]

Yijie Han. 2020. Sorting real numbers in O(n &sqrt;log n) time and linear space. Algorithmica 82, 4 (2020), 966--978.

[59]

Yijie Han and Mikkel Thorup. 2002. Integer sorting in O(n &sqrt;log log n) expected time and linear space. In Proceedings of the 43rd Symposium on Foundations of Computer Science (FOCS’02). 135--144.

Digital Library

[60]

Steffen Heinz, Justin Zobel, and Hugh E. Williams. 2002. Burst tries: A fast, efficient data structure for string keys. ACM Trans. Info. Syst. 20, 2 (2002), 192--223.

Digital Library

[61]

Wing-Kai Hon, Tak Wah Lam, Rahul Shah, Siu-Lung Tam, and Jeffrey Scott Vitter. 2011. Cache-oblivious index for approximate string matching. Theor. Comput. Sci. 412, 29 (2011), 3579--3588.

Digital Library

[62]

Marek Karpinski and Yakov Nekrich. 2005. Predecessor queries in constant time? In Proceedings of the 13th Annual European Symposium on Algorithms (ESA’05). 238--248.

Digital Library

[63]

David G. Kirkpatrick and Stefan Reisch. 1984. Upper bounds for sorting integers on random access machines. Theor. Comput. Sci. 28 (1984), 263--276.

[64]

Donald E. Knuth. 1973. The Art of Computer Programming, Volume III: Sorting and Searching. Addison-Wesley.

[65]

Donald E. Knuth. 1977. Notes on the van Emde Boas Construction of Priority Deques: An Instructive Use of Recursion. Classroom notes. Stanford University.

[66]

Tsvi Kopelowitz. 2012. On-line indexing for general alphabets via predecessor queries on subsets of an ordered list. In Proceedings of the 53rd Annual IEEE Symposium on Foundations of Computer Science (FOCS’12). 283--292.

Digital Library

[67]

A. Levitin. 2007. Introduction to the Design and Analysis of Algorithms (2nd ed.). Addison-Wesley.

[68]

Mingmou Liu and Huacheng Yu. 2020. Lower bound for succinct range minimum query. CoRR abs/2004.05738.

[69]

Kurt Mehlhorn and Stefan Näher. 1990. Bounded ordered dictionaries in O(log log N) time and O(n) space. Info. Process. Lett. 35, 4 (1990), 183--189.

Digital Library

[70]

Kurt Mehlhorn and Athanasios K. Tsakalidis. 1993. Dynamic interpolation search. J. ACM 40, 3 (1993), 621--634.

Digital Library

[71]

Peter Bro Miltersen. 1994. Lower bounds for union-split-find related problems on random access machines. In Proceedings of the 26th Annual ACM Symposium on Theory of Computing (STOC’94). 625--634.

Digital Library

[72]

Peter Bro Miltersen, Noam Nisan, Shmuel Safra, and Avi Wigderson. 1998. On data structures and asymmetric communication complexity. J. Comput. Syst. Sci. 57, 1 (1998), 37--49.

Digital Library

[73]

Christian Worm Mortensen. 2006. Fully dynamic orthogonal range reporting on RAM. SIAM J. Comput. 35, 6 (2006), 1494--1525.

Digital Library

[74]

Christian Worm Mortensen, Rasmus Pagh, and Mihai Patrascu. 2005. On dynamic range reporting in one dimension. In Proceedings of the 37th Annual ACM Symposium on Theory of Computing (STOC’05). 104--111.

Digital Library

[75]

J. Ian Munro. 1996. Tables. In Proceedings of the 16th Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS’96). 37--42.

[76]

Nicholas Nash and David Gregg. 2010. Comparing integer data structures for 32- and 64-bit keys. ACM J. Exper. Algor. 15 (2010).

[77]

Mihai Patrascu. 2008. Lower Bound Techniques for Data Structures. Ph.D. Dissertation. Massachusetts Institute of Technology, USA.

[78]

Mihai Patrascu. 2008. Succincter. In Proceedings of the 49th Annual IEEE Symposium on Foundations of Computer Science (FOCS’08). 305--313.

[79]

Mihai Patrascu and Erik D. Demaine. 2004. Tight bounds for the partial-sums problem. In Proceedings of the 15th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’04), J. Ian Munro (Ed.). SIAM, 20--29.

[80]

Mihai Patrascu and Erik D. Demaine. 2006. Logarithmic lower bounds in the cell-probe model. SIAM J. Comput. 35, 4 (2006), 932--963.

Digital Library

[81]

Mihai Patrascu and Mikkel Thorup. 2006. Time-space trade-offs for predecessor search. In Proceedings of the 38th Annual ACM Symposium on Theory of Computing (STOC’06). 232--240.

[82]

Mihai Patrascu and Mikkel Thorup. 2007. Randomization does not help searching predecessors. In Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’07). 555--564.

[83]

Mihai Patrascu and Mikkel Thorup. 2014. Dynamic integer sets with optimal rank, select, and predecessor search. In Proceedings of the 55th IEEE Annual Symposium on Foundations of Computer Science (FOCS’14). 166--175.

Digital Library

[84]

Mihai Patrascu and Emanuele Viola. 2010. Cell-probe lower bounds for succinct partial sums. In Proceedings of the 21st Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’10). 117--122.

[85]

David A. Patterson and John L. Hennessy. 2012. Computer Organization and Design—The Hardware/Software Interface (5th ed.). Academic Press.

[86]

W. Paul and Janos Simon. 1980. Decision trees and random access machines. Logic Algor. 30 (1980), 331--340.

[87]

Giulio Ermanno Pibiri and Rossano Venturini. 2017. Dynamic Elias-Fano representation. In Proceedings of the 28th Annual Symposium on Combinatorial Pattern Matching (CPM’17). 30:1--30:14.

[88]

William Pugh. 1990. Skip lists: A probabilistic alternative to balanced trees. Commun. ACM 33, 6 (1990), 668--676.

Digital Library

[89]

Naila Rahman, Richard Cole, and Rajeev Raman. 2001. Optimised predecessor data structures for internal memory. In Proceedings of the 5th International Workshop on Algorithm Engineering (WAE’01). 67--78.

Digital Library

[90]

Rajeev Raman, Venkatesh Raman, and Srinivasa Rao Satti. 2007. Succinct indexable dictionaries with applications to encoding k-ary trees, prefix sums and multisets. ACM Trans. Algor. 3, 4 (2007), 43.

Digital Library

[91]

Milan Ruzic. 2008. Constructing efficient dictionaries in close to sorting time. In Proceedings of the 35th International Colloquium on Automata, Languages and Programming (ICALP’08). 84--95.

[92]

Milan Ruzic. 2009. Making deterministic signatures quickly. ACM Trans. Algor. 5, 3 (2009), 26:1--26:26.

[93]

Pranab Sen and Srinivasan Venkatesh. 2008. Lower bounds for predecessor searching in the cell probe model. J. Comput. Syst. Sci. 74, 3 (2008), 364--385.

Digital Library

[94]

Qingmin Shi and Joseph JaJa. 2003. Fast Fractional Cascading and Its Applications. Technical Report. University of Maryland, College Park, MD.

[95]

Daniel Dominic Sleator and Robert Endre Tarjan. 1983. Self-adjusting binary trees. In Proceedings of the 15th Annual ACM Symposium on Theory of Computing (STOC’83). 235--245.

Digital Library

[96]

Mikkel Thorup. 1998. Faster deterministic sorting and priority queues in linear space. In Proceedings of the 9th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’98). 550--555.

[97]

Mikkel Thorup. 2003. On AC⁰ implementations of fusion trees and atomic heaps. In Proceedings of the 14th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA’03). 699--707.

[98]

Mikkel Thorup. 2007. Equivalence between priority queues and sorting. J. ACM 54, 6 (2007), 28.

Digital Library

[99]

Peter van Emde Boas. 1977. Preserving order in a forest in less than logarithmic time and linear space. Info. Process. Lett. 6, 3 (1977), 80--82.

[100]

Peter van Emde Boas. 2013. Thirty nine years of stratified trees. In Proceedings of the 2nd International Symposium on Computing in Informatics and Mathematics (ICSIM’13). 1--14.

[101]

Peter van Emde Boas, R. Kaas, and E. Zijlstra. 1977. Design and implementation of an efficient priority queue. Math. Syst. Theory 10 (1977), 99--127.

[102]

Dan E. Willard. 1983. Log-logarithmic worst-case range queries are possible in space Θ(N). Info. Process. Lett. 17, 2 (1983), 81--84.

[103]

Dan E. Willard. 2000. Examining computational geometry, van Emde Boas trees, and hashing from the perspective of the fusion tree. SIAM J. Comput. 29, 3 (2000), 1030--1049.

Digital Library

[104]

Paolo Ferragina and Giorgio Vinciguerra. 2020. The PGM-index: A fully-dynamic compressed learned index with provable worst-case bounds. Proc. of the VLDB Endowment 13, 8 (2020), 1162--1175.

Digital Library

Cited By

Costa MFerragina PVinciguerra G(2024)Grafite: Taming Adversarial Queries with Optimal Range FiltersProceedings of the ACM on Management of Data10.1145/36392582:1(1-23)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639258
Cenzato DLipták Z(2024)A survey of BWT variants for string collectionsBioinformatics10.1093/bioinformatics/btae33340:7Online publication date: 24-May-2024
https://doi.org/10.1093/bioinformatics/btae333
Bille PGørtz IStordalen T(2024)Predecessor on the Ultra-Wide Word RAMAlgorithmica10.1007/s00453-023-01193-186:5(1578-1599)Online publication date: 10-Jan-2024
https://doi.org/10.1007/s00453-023-01193-1
Show More Cited By

Index Terms

Predecessor Search
1. Theory of computation
  1. Design and analysis of algorithms
    1. Data structures design and analysis
      1. Predecessor queries
      2. Sorting and searching

Recommendations

Time-space trade-offs for predecessor search
STOC '06: Proceedings of the thirty-eighth annual ACM symposium on Theory of Computing

We develop a new technique for proving cell-probe lower bounds for static data structures. Previous lower bounds used a reduction to communication games, which was known not to be tight by counting arguments. We give the first lower bound for an ...
Dynamic Integer Sets with Optimal Rank, Select, and Predecessor Search
FOCS '14: Proceedings of the 2014 IEEE 55th Annual Symposium on Foundations of Computer Science

We present a data structure representing a dynamic set S of w-bit integers on a w-bit word RAM. With |S| = n and w ≥ log n and space O(n), we support the following standard operations in O(log n/log w) time: insert(x) sets S = S + {x}. delete(x) sets S =...
Randomized Approximate Nearest Neighbor Search with Limited Adaptivity
SPAA '16: Proceedings of the 28th ACM Symposium on Parallelism in Algorithms and Architectures

We study the problem of approximate nearest neighbor search in $d$-dimensional Hamming space {0,1}^d. We study the complexity of the problem in the famous cell-probe model, a classic model for data structures. We consider algorithms in the cell-probe ...

Comments

Information & Contributors

Information

Published In

cover image ACM Computing Surveys

ACM Computing Surveys Volume 53, Issue 5

September 2021

782 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/3426973

Editor:
Albert Zomaya
University of Sydney, Austraila

Issue’s Table of Contents

Copyright © 2020 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2020

Accepted: 01 June 2020

Revised: 01 May 2020

Received: 01 February 2019

Published in CSUR Volume 53, Issue 5

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Survey
Research
Refereed

Funding Sources

Millennium Institute for Foundational Research on Data (IMFD), Chile, and by Project CONICYT

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

12
Total Citations
View Citations
651
Total Downloads

Downloads (Last 12 months)231
Downloads (Last 6 weeks)67

Reflects downloads up to 18 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Costa MFerragina PVinciguerra G(2024)Grafite: Taming Adversarial Queries with Optimal Range FiltersProceedings of the ACM on Management of Data10.1145/36392582:1(1-23)Online publication date: 26-Mar-2024
https://dl.acm.org/doi/10.1145/3639258
Cenzato DLipták Z(2024)A survey of BWT variants for string collectionsBioinformatics10.1093/bioinformatics/btae33340:7Online publication date: 24-May-2024
https://doi.org/10.1093/bioinformatics/btae333
Bille PGørtz IStordalen T(2024)Predecessor on the Ultra-Wide Word RAMAlgorithmica10.1007/s00453-023-01193-186:5(1578-1599)Online publication date: 10-Jan-2024
https://doi.org/10.1007/s00453-023-01193-1
Liu XKong JLuo DXiong NXu GChen X(2023)An Intelligent Semi-Honest System for Secret Matching against Malicious AdversariesElectronics10.3390/electronics1212261712:12(2617)Online publication date: 10-Jun-2023
https://doi.org/10.3390/electronics12122617
Kociumaka TNavarro GPrezza N(2023)Toward a Definitive Compressibility Measure for Repetitive SequencesIEEE Transactions on Information Theory10.1109/TIT.2022.322438269:4(2074-2092)Online publication date: 1-Apr-2023
https://dl.acm.org/doi/10.1109/TIT.2022.3224382
Arimura HInenaga SKobayashi YNakashima YSue M(2023)Optimally Computing Compressed Indexing Arrays Based on the Compact Directed Acyclic Word GraphString Processing and Information Retrieval10.1007/978-3-031-43980-3_3(28-34)Online publication date: 26-Sep-2023
https://dl.acm.org/doi/10.1007/978-3-031-43980-3_3
Pissis SShekelyan MLiu CLoukides G(2023)Frequency-Constrained Substring ComplexityString Processing and Information Retrieval10.1007/978-3-031-43980-3_28(345-352)Online publication date: 20-Sep-2023
https://doi.org/10.1007/978-3-031-43980-3_28
Boffa AFerragina PVinciguerra G(2022)A Learned Approach to Design Compressed Rank/Select Data StructuresACM Transactions on Algorithms10.1145/352406018:3(1-28)Online publication date: 17-Mar-2022
https://dl.acm.org/doi/10.1145/3524060
Kieffer JYang E(2022)Survey of Grammar-Based Data Structure CompressionIEEE BITS the Information Theory Magazine10.1109/MBITS.2022.3210891(1-12)Online publication date: 2022
https://doi.org/10.1109/MBITS.2022.3210891
Ferragina PManzini GVinciguerra G(2022)Compressing and Querying Integer Dictionaries Under Linearities and RepetitionsIEEE Access10.1109/ACCESS.2022.322152010(118831-118848)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3221520
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Figures

Tables

Media

View Issue’s Table of Contents