TY - GEN

T1 - Almost linear time computation of maximal repetitions in run length encoded strings

AU - Fujishige, Yuta

AU - Nakashima, Yuto

AU - Inenaga, Shunsuke

AU - Bannai, Hideo

AU - Takeda, Masayuki

N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

PY - 2017/12/1

Y1 - 2017/12/1

N2 - We consider the problem of computing all maximal repetitions contained in a string that is given in run-length encoding. Given a run-length encoding of a string, we show that the maximum number of maximal repetitions contained in the string is at most m+k-1, where m is the size of the run-length encoding, and k is the number of run-length factors whose exponent is at least 2. We also show an algorithm for computing all maximal repetitions in O(m α (m)) time and O(m) space, where α denotes the inverse Ackermann function.

AB - We consider the problem of computing all maximal repetitions contained in a string that is given in run-length encoding. Given a run-length encoding of a string, we show that the maximum number of maximal repetitions contained in the string is at most m+k-1, where m is the size of the run-length encoding, and k is the number of run-length factors whose exponent is at least 2. We also show an algorithm for computing all maximal repetitions in O(m α (m)) time and O(m) space, where α denotes the inverse Ackermann function.

UR - http://www.scopus.com/inward/record.url?scp=85038564653&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85038564653&partnerID=8YFLogxK

U2 - 10.4230/LIPIcs.ISAAC.2017.33

DO - 10.4230/LIPIcs.ISAAC.2017.33

M3 - Conference contribution

AN - SCOPUS:85038564653

T3 - Leibniz International Proceedings in Informatics, LIPIcs

BT - 28th International Symposium on Algorithms and Computation, ISAAC 2017

A2 - Tokuyama, Takeshi

A2 - Okamoto, Yoshio

PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing

T2 - 28th International Symposium on Algorithms and Computation, ISAAC 2017

Y2 - 9 December 2017 through 22 December 2017

ER -