{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dynamic-packed-compact-tries-revisited","title":"c-trie++: A Dynamic Trie Tailored for Fast Prefix Searches","arxiv_id":"1904.07467","date":"2019-04-16","proceeding":null,"authors":["Kazuya Tsuruta","Dominik Köppl","Shunsuke Kanda","Yuto Nakashima","Shunsuke Inenaga","Hideo Bannai","Masayuki Takeda"],"abstract":"Given a dynamic set $K$ of $k$ strings of total length $n$ whose characters are drawn from an alphabet of size $\\sigma$, a keyword dictionary is a data structure built on $K$ that provides locate, prefix search, and update operations on $K$. Under the assumption that $\\alpha = w / \\lg \\sigma$ characters fit into a single machine word $w$, we propose a keyword dictionary that represents $K$ in $n \\lg \\sigma + \\Theta(k \\lg n)$ bits of space, supporting all operations in $O(m / \\alpha + \\lg \\alpha)$ expected time on an input string of length $m$ in the word RAM model. This data structure is underlined with an exhaustive practical evaluation, highlighting the practical usefulness of the proposed data structure, especially for prefix searches - one of the most elementary keyword dictionary operations.","url_abs":"https://arxiv.org/abs/1904.07467v3","url_pdf":"https://arxiv.org/pdf/1904.07467v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"dynamic-packed-compact-tries-revisited","repo_url":"https://gitlab.com/habatakitai/ctriepp","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}