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Sensitivity of string compressors and repetitiveness measures

Published 19 Jul 2021 in cs.DS | (2107.08615v6)

Abstract: The sensitivity of a string compression algorithm CC asks how much the output size C(T)C(T) for an input string TT can increase when a single character edit operation is performed on TT. This notion enables one to measure the robustness of compression algorithms in terms of errors and/or dynamic changes occurring in the input string. In this paper, we analyze the worst-case multiplicative sensitivity of string compression algorithms, which is defined by $\max_{T \in \Sigma<sup>n}{C(T&#39;)/C(T)</sup> : ed(T, T&#39;) = 1}$, where $ed(T, T&#39;)$ denotes the edit distance between TT and $T&#39;$. For the most common versions of the Lempel-Ziv 77 compressors, we prove that the worst-case multiplicative sensitivity is upper bounded by a small constant, and give matching lower bounds. We generalize these results to the smallest bidirectional scheme bb. In addition, we show that the sensitivity of a grammar-based compressor called GCIS is also a small constant. Further, we extend the notion of the worst-case sensitivity to string repetitiveness measures such as the smallest string attractor size γ\gamma and the substring complexity δ\delta, and show that the worst-case sensitivity of δ\delta is also a small constant. These results contrast with the previously known related results such that the size z78z_{\rm 78} of the Lempel-Ziv 78 factorization can increase by a factor of Ω(n<sup>1/4)\Omega(n<sup>{1/4}) [Lagarde and Perifel, 2018], and the number rr of runs in the Burrows-Wheeler transform can increase by a factor of Ω(logn)\Omega(\log n) [Giuliani et al., 2021] when a character is prepended to an input string of length nn. By applying our sensitivity bounds of δ\delta or the smallest grammar to known results (c.f. [Navarro, 2021]), some non-trivial upper bounds for the sensitivities of important string compressors and repetitiveness measures including γ\gamma, rr, LZ-End, RePair, LongestMatch, and AVL-grammar are derived.

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