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cs.DS updates on arXiv.org

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Sensitivity of string compressors and repetitiveness meas...
Tooru Akagi, Mitsuru Funakoshi, Shunsuke Inenaga · 2021-07-19 · via cs.DS updates on arXiv.org

The sensitivity of a string compression algorithm $C$ asks how much the output size $C(T)$ for an input string $T$ can increase when a single character edit operation is performed on $T$. 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 $\max_{T \in Σ^n}\{C(T')/C(T) : ed(T, T') = 1\}$, where $ed(T, T')$ denotes the edit distance between $T$ and $T'$. 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 $b$. 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 $γ$ and the substring complexity $δ$, and show that the worst-case sensitivity of $δ$ is also a small constant. These results contrast with the previously known related results such that the size $z_{\rm 78}$ of the Lempel-Ziv 78 factorization can increase by a factor of $Ω(n^{1/4})$ [Lagarde and Perifel, 2018], and the number $r$ of runs in the Burrows-Wheeler transform can increase by a factor of $Ω(\log n)$ [Giuliani et al., 2021] when a character is prepended to an input string of length $n$. By applying our sensitivity bounds of $δ$ 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 $γ$, $r$, LZ-End, RePair, LongestMatch, and AVL-grammar are derived.