Computing the LZ-End parsing: Easy to implement and practically efficient
<|reference_start|>Computing the LZ-End parsing: Easy to implement and practically efficient: The LZ-End parsing [Kreft & Navarro, 2011] of an input string yields compression competitive with the popular Lempel-Ziv 77 scheme, but also allows for efficient random access. Kempa and Kosolobov showed that the parsing can be computed in time and space linear in the input length [Kempa & Kosolobov, 2017], however, the corresponding algorithm is hardly practical. We put the spotlight on their suboptimal algorithm that computes the parsing in time $\mathcal{O}(n \lg\lg n)$. It requires a comparatively small toolset and is therefore easy to implement, but at the same time very efficient in practice. We give a detailed and simplified description with a full listing that incorporates undocumented tricks from the original implementation, but also uses lazy evaluation to reduce the workload in practice and requires less working memory by removing a level of indirection. We legitimize our algorithm in a brief benchmark, obtaining the parsing faster than the state of the art.<|reference_end|>
@article{dinklage2024computing,
    title={Computing the LZ-End parsing: Easy to implement and practically
  efficient},
    author={Patrick Dinklage},
    journal={arXiv preprint arXiv:2409.07840},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.07840},
    primaryClass={cs.DS}
}