arXiv (Cornell University) · 2014 · 14 citations · 3 references
ComputingComputer ScienceMathematicsAlgorithmsCombinatoricsTheory Of ComputationAlgorithm AnalysisAlgorithmic ComplexityComputational ComplexityRandomized ComplexityRandomized ComputationTime ComplexityComparison ComplexityComplexity Of String AlgorithmsDecision Tree ComplexityDecision-tree AnalysisLower Bound ComputationWorst-case BoundsWorst-case Complexity
The complexity of computing the Lempel-Ziv factorization and the set of all runs (= maximal repetitions) is studied in the decision tree model of computation over ordered alphabet. It is known that both these problems can be solved by RAM algorithms in $O(n\logσ)$ time, where $n$ is the length of the input string and $σ$ is the number of distinct letters in it. We prove an $Ω(n\logσ)$ lower bound on the number of comparisons required to construct the Lempel-Ziv factorization and thereby conclude that a popular technique of computation of runs using the Lempel-Ziv factorization cannot achieve an $o(n\logσ)$ time bound. In contrast with this, we exhibit an $O(n)$ decision tree algorithm finding all runs in a string. Therefore, in the decision tree model the runs problem is easier than the Lempel-Ziv factorization. Thus we support the conjecture that there is a linear RAM algorithm finding all runs.
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Finding maximal repetitions in a word in linear time
Roman Kolpakov, Grégory Kucherov · 2003 · 324 citations
Maxime Crochemore, Lucian Ilie, Liviu Tinta · Theoretical Computer Science · 2010 · 36 citations