Papers for

network system engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Union-find data structure supports constant-time deletions with efficient queries

Union-Find with Constant-Time Deletions Across the Optimal Worst-Case Tradeoff

Abstract: We consider union-find with deletions, where the representation and the cost of a query must depend on the current number of live elements rather than on the number of elements ever created. For every integer parameter $k\ge 2$, we give a linear-space data structure supporting $\mathsf{MakeSet}$ in $O(1)$ worst-case time, $\mathsf{Union}$ in $O(k)$ worst-case time, $\mathsf{Delete}$ in $O(1)$ worst-case time, and $\mathsf{Find}$ in $O\left(1+\frac{\log n}{\log k}\right)$ worst-case time for a set containing $n$ live elements. A deletion is given only an element handle, not the identifier of its current set. The construction separates global rank growth from local deletion repair. A logical set is represented by fewer than $k$ disjoint ranked trees. Equal-level trees are collected without physical linking until $k$ certificates are available, at which point one base-$k$ carry is performed in $O(k)$ time. Each member tree uses a strengthened form of the full/reduced local rebuilding scheme of Ben-Amram and Yoffe. A $q$-ary value argument, with $q=3/2$, couples the local trees to the base-$k$ certificates and yields the stated current-size height bound. A small but essential rule handles high-rank stars, a state that the base-$k$ carry can create but that does not arise directly in the binary-rank construction underlying the earlier local scheme.

Sat 19 SeptData Structures and Algorithms
The gist
This work improves a data structure called union-find that helps group elements and quickly tell which group an element belongs to. The authors focus on making sure that removing elements is always very fast, even as the number of elements changes. They accomplish this by organizing groups into several ranked trees and managing updates carefully. Their method balances the work needed to join groups, remove elements, and find group memberships efficiently, depending on how many elements remain active.
Open → 2609.22892v1