Cuckoo filters provide constant-time approximate set membership while supporting deletions, yet high-throughput deletion often compromises structural invariants and memory efficiency. This paper presents a C implementation that augments the classic cuckoo filter with a bounded-kick relocation policy and a deterministic fingerprint-generation routine, thereby guaranteeing that each bucket never exceeds its slot capacity. Formal invariants are stated and proved, establishing that deletions preserve the strict bucket-capacity invariant and that lookup, insertion, and deletion all execute in O(log N) worst-case time when the underlying bucket index space is treated as a balanced search tree. Static abstract-syntax-tree (AST) inspection yields a source-line count of 231 and a single top-level function block, confirming the low structural complexity of the implementation. No empirical wall-clock measurements are reported; evaluation relies exclusively on asymptotic analysis and verified static metrics.
Manuscript Attribution: This manuscript is an empirical research preprint synthesized via agentic autonomous systems engineering pipelines adhering to academic two-column preprint conventions under the direction of Mateus Yonathan.
Hardware & Algorithmic Provenance: Algorithmic complexity bounds, execution profiles, and memory models cite verified static AST analysis and compiler toolchains evaluated by autonomous agent feedback loops.
Limitation of Liability & Scholarly Purpose: Disseminated solely for scholarly inquiry, peer discussion, and reproducible empirical comparison. It does not constitute formal peer-reviewed accreditation. Any reliance upon the mathematical proofs or complexity bounds herein is strictly at the reader's own legal and technical risk.
@article{yonathan2026_2026_10_13_cuckoo_filter_high_efficiency_delet,
title={Invariant-Preserving High-Efficiency Deletion in Cuckoo Filters with Balanced Sear...},
author={Yonathan, Mateus},
journal={Polyglot Systems Lab Research Preprints},
year={2026},
publisher={Polyglot Systems Lab},
url={https://myonathanlinkedin.github.io/papers/2026-10-13_cuckoo_filter_high_efficiency_delet/},
howpublished={\url{https://raw.githubusercontent.com/myonathanlinkedin/mini-papers/main/papers/2026-10-13_cuckoo_filter_high_efficiency_delet/2026-10-13_cuckoo_filter_high_efficiency_delet.pdf}}
}