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DOI: 10.4230/LIPIcs.SEA.2026.5

BuffCut: Prioritized Buffered Streaming Graph Partitioning

Authors: Linus Baumgärtner, Adil Chhabra, Marcelo Fonseca Faraj, and Christian Schulz

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract

Streaming graph partitioners enable resource-efficient and massively scalable partitioning, but one-pass assignment heuristics are highly sensitive to stream order and often yield substantially higher edge cuts than in-memory methods. We present BuffCut, a buffered streaming partitioner that narrows this quality gap, particularly when stream ordering is adversarial, by combining prioritized buffering with batch-wise multilevel assignment. BuffCut maintains a bounded priority buffer to delay poorly informed decisions and regulate the order in which nodes are considered for assignment. It incrementally constructs high-locality batches of configurable size by iteratively inserting the highest-priority nodes from the buffer into the batch, effectively recovering locality structure from the stream. Each batch is then assigned via a multilevel partitioning algorithm. Experiments on diverse real-world and synthetic graphs show that BuffCut consistently outperforms state-of-the-art buffered streaming methods. Compared to the strongest prioritized buffering baseline, BuffCut achieves 20.8% fewer edge cuts while running 2.9× faster and using 11.3× less memory. Against the next-best batched method, it reduces edge cut by 15.8% with only modest overheads of 1.8× runtime and 1.09× memory.

Cite as

Linus Baumgärtner, Adil Chhabra, Marcelo Fonseca Faraj, and Christian Schulz. BuffCut: Prioritized Buffered Streaming Graph Partitioning. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 5:1-5:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{baumgartner_et_al:LIPIcs.SEA.2026.5,
  author =	{Baumg\"{a}rtner, Linus and Chhabra, Adil and Faraj, Marcelo Fonseca and Schulz, Christian},
  title =	{{BuffCut: Prioritized Buffered Streaming Graph Partitioning}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{5:1--5:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.5},
  URN =		{urn:nbn:de:0030-drops-260097},
  doi =		{10.4230/LIPIcs.SEA.2026.5},
  annote =	{Keywords: graph partitioning, streaming, online, buffered, prioritized partitioning}
}

Document

DOI: 10.4230/LIPIcs.SEA.2026.13

Practical Parallel Block Tree Construction

Authors: Robert Clausecker, Florian Kurpicz, and Etienne Palanga

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract

The block tree [Belazzougui et al., J. Comput. Syst. Sci. '21] is a compressed representation of a length-n text that supports access, rank, and select queries while requiring only O(z log n/z) words of space, where z is the number of Lempel-Ziv factors of the text. In other words, its space requirements are asymptotically comparable to those of the compressed text itself. In practice, block trees offer query performance comparable to that of state-of-the-art compressed rank and select indices. However, their construction is significantly slower, and the fastest known construction algorithms additionally require a significant amount of working memory. To address these limitations, we propose fast and lightweight parallel algorithms for the efficient construction of block trees. Our algorithm achieves similar construction speed than the currently fastest block tree construction algorithm on a single core and is up to eight times faster using 64 cores, while requiring an order of magnitude less memory. Overall, we achieve a speedup of up to 15.5 on 64 cores, which is in line with the parallel construction of the Lempel-Ziv compression.

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Robert Clausecker, Florian Kurpicz, and Etienne Palanga. Practical Parallel Block Tree Construction. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 13:1-13:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{clausecker_et_al:LIPIcs.SEA.2026.13,
  author =	{Clausecker, Robert and Kurpicz, Florian and Palanga, Etienne},
  title =	{{Practical Parallel Block Tree Construction}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{13:1--13:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.13},
  URN =		{urn:nbn:de:0030-drops-260175},
  doi =		{10.4230/LIPIcs.SEA.2026.13},
  annote =	{Keywords: block tree, shared memory, compression, SIMD, Karp-Rabin fingerprints}
}

Document

DOI: 10.4230/LIPIcs.SEA.2026.10

Compressing Highly Repetitive Binary Trees with an Application to Range Minimum Queries

Authors: Gabriel Carmona and Filippo Lari

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract

Tree compression is a well-studied area that aims at reducing the size of tree representations by exploiting different forms of repetition. While the underlying theory is well understood, there is still significant room for experimental investigation, particularly in the design of compressed representations that efficiently support navigational queries. In this work, we address the problem of designing, engineering, and experimentally evaluating a compression technique for unlabeled binary trees based on repeated subtrees, yielding the minimal Directed Acyclic Graph (DAG) of the input tree. We show how this representation can be computed in linear time and space directly from a succinct encoding of the tree, and how it can be augmented with compact auxiliary data structures to support Lowest Common Ancestor (LCA) queries. When the input tree is the Cartesian tree of an array, LCA queries can be used to answer Range Minimum Queries (RMQs) on the underlying array. This is particularly relevant in the encoding model, where the array is not accessible at query time, and a space lower bound of 2n-O(log n) bits is known. Given the numerous applications of RMQs, we use this problem as a case study for our experimental evaluation, testing our implementation on 11 real-world datasets. Our experiments show that, on almost every dataset, our implementation is the most space-efficient, using as few as 0.11n bits, while still delivering practical query times.

Cite as

Gabriel Carmona and Filippo Lari. Compressing Highly Repetitive Binary Trees with an Application to Range Minimum Queries. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 10:1-10:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{carmona_et_al:LIPIcs.SEA.2026.10,
  author =	{Carmona, Gabriel and Lari, Filippo},
  title =	{{Compressing Highly Repetitive Binary Trees with an Application to Range Minimum Queries}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{10:1--10:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.10},
  URN =		{urn:nbn:de:0030-drops-260140},
  doi =		{10.4230/LIPIcs.SEA.2026.10},
  annote =	{Keywords: tree compression, range minimum query, compact data structures, algorithm engineering, experimental evaluation}
}

Document

DOI: 10.4230/LIPIcs.SEA.2026.24

ZOR Filters: Fast and Smaller Than Fuse Filters

Authors: Antoine Limasset

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract

Probabilistic membership filters support fast approximate membership queries with controlled false-positive probability ε and are widely used across storage, analytics, networking, and bioinformatics [Chang et al., 2008; Niv Dayan et al., 2018; Broder and Mitzenmacher, 2004; Harris and Medvedev, 2020; Marchet and Limasset, 2023; Chikhi et al., 2025; Hernandez-Courbevoie et al., 2025]. In the static setting, low-overhead methods such as XOR, Fuse, and BuRR have been proposed [Graf and Lemire, 2020; Graf and Lemire, 2022; Dillinger et al., 2022; Ulrich and Renard, 2023]. Among these, Fuse filters are known for near-optimal query throughput. For XOR/Fuse-style peeling constructions, however, build success is only high probability, which complicates deterministic builds. We introduce ZOR filters, a deterministic continuation of XOR/Fuse-style constructions that guarantees termination while preserving the same XOR-based query mechanism. ZOR replaces restart-on-failure with deterministic peeling that abandons a small fraction of keys, and restores false-positive-only semantics by storing the remainder in a compact auxiliary structure. In our experiments, the abandoned fraction drops below 1% for moderate arity (e.g., N ≥ 5), so the auxiliary handles a negligible fraction of keys. As a result, ZOR filters can be substantially more memory-efficient than Fuse filters, with overhead below 1%, while not yet matching the near-optimal overhead of BuRR (below 0.1%). In query performance, ZOR-pure is close to Fuse and faster than BuRR on positive queries, while the complete interleaved variant trades additional negative-query latency for deterministic continuation. Relative to optimised Fuse/BuRR implementations [Graf and Lemire, 2022; Dillinger et al., 2022], the current ZOR prototype remains slower in construction because deterministic peeling requires explicit incidence handling; reducing this construction gap is an important direction for future work.

Cite as

Antoine Limasset. ZOR Filters: Fast and Smaller Than Fuse Filters. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 24:1-24:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{limasset:LIPIcs.SEA.2026.24,
  author =	{Limasset, Antoine},
  title =	{{ZOR Filters: Fast and Smaller Than Fuse Filters}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{24:1--24:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.24},
  URN =		{urn:nbn:de:0030-drops-260281},
  doi =		{10.4230/LIPIcs.SEA.2026.24},
  annote =	{Keywords: Data structure, Approximate Set Membership, Static filter}
}

Document

DOI: 10.4230/LIPIcs.SEA.2026.20

QuadRank: Engineering a High Throughput Rank

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 371, 24th International Symposium on Experimental Algorithms (SEA 2026)

Abstract

Motivation. Given a text, a query rank(q, c) counts the number of occurrences of character c among the first q characters of the text. Space-efficient methods to answer these rank queries form an important building block in many succinct data structures. For example, the FM-index [Ferragina and Manzini, 2000] is a widely used data structure that uses rank queries to locate all occurrences of a pattern in a text. In bioinformatics applications, the goal is usually to process large inputs as fast as possible. Thus, data structures should have high throughput when used with many threads. Contributions. We first survey existing results on rank data structures. For the σ = 2 binary alphabet, we then develop BiRank, which has 3.28% space overhead. BiRank merges the central ideas of two recent papers: (1) we interleave (inline) offsets in each cache line of the underlying bit vector [Laws et al., 2024], reducing cache misses, and (2) these offsets are to the middle of each block so that only half of each needs popcounting [Gottlieb and Reinert, 2025]. In QuadRank (14.4% overhead), we extend these techniques to the σ = 4 (DNA) alphabet. Both data structures typically require only a single cache miss per query, making them highly suitable for high-throughput and memory-bound settings. To enable efficient batch-processing, we support prefetching the cache lines required to answer upcoming queries. Results. BiRank and QuadRank are around 1.5× and 2× faster than similar-overhead methods that do not use interleaving. Prefetching gives an additional 2× speedup, at which point the dual-channel DDR4 RAM bandwidth becomes a hard limit on the total throughput. With prefetching, both methods outperform all other methods apart from SPIDER [Laws et al., 2024] by 2×. When using QuadRank with prefetching in a toy count-only FM-index, QuadFm, this results in a smaller size and up to 4× speedup over Genedex, a state-of-the-art batching FM-index implementation. Conclusion. Optimizing data structures for high throughput, by minimizing cache misses and branch-misses and adding support for prefetching, can result in significant speedups when benchmarks are adjusted accordingly.

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Ragnar Groot Koerkamp. QuadRank: Engineering a High Throughput Rank. In 24th International Symposium on Experimental Algorithms (SEA 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 371, pp. 20:1-20:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{grootkoerkamp:LIPIcs.SEA.2026.20,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{QuadRank: Engineering a High Throughput Rank}},
  booktitle =	{24th International Symposium on Experimental Algorithms (SEA 2026)},
  pages =	{20:1--20:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-422-2},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{371},
  editor =	{Aum\"{u}ller, Martin and Finocchi, Irene},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2026.20},
  URN =		{urn:nbn:de:0030-drops-260248},
  doi =		{10.4230/LIPIcs.SEA.2026.20},
  annote =	{Keywords: Rank, Succinct Data Structures, Cache Performance, Prefetching}
}

Document

DOI: 10.4230/LIPIcs.SWAT.2026.14

Orthogonal Strip Partitioning of Polygons: Lattice-Theoretic Algorithms and Lower Bounds

Authors: Jaehoon Chung

Published in: LIPIcs, Volume 370, 20th Scandinavian Symposium on Algorithm Theory (SWAT 2026)

Abstract

We study a variant of a polygon partition problem, introduced by Chung, Iwama, Liao, and Ahn [ISAAC'25]. Given orthogonal unit vectors 𝐮,𝐯 ∈ ℝ² and a polygon P with n vertices, we partition P into connected pieces by cuts parallel to 𝐯 such that each resulting subpolygon has width at most one in direction 𝐮. We consider the value version, which asks for the minimum number of strips, and the reporting version, which outputs a compact encoding of the cuts in an optimal strip partition. We give efficient algorithms and lower bounds for both versions on three classes of polygons of increasing generality: convex, simple, and self-overlapping. For convex polygons, we solve the value version in O(log n) time and the reporting version in O(h log (1 + n/h)) time, where h is the width of P in direction 𝐮. We prove matching lower bounds in the decision-tree model, showing that the reporting algorithm is input-sensitive optimal with respect to h. For simple polygons, we present O(n log n)-time, O(n)-space algorithms for both versions and prove an Ω(n) lower bound. For self-overlapping polygons, we extend the approach for simple polygons to obtain O(n log n)-time, O(n)-space algorithms for both versions, and we prove a matching Ω(n log n) lower bound in the algebraic computation-tree model via a reduction from the δ-closeness problem. Our approach relies on a lattice-theoretic formulation of the problem. We represent strip partitions as antichains of intervals in the Clarke-Cormack-Burkowski lattice, originally developed for minimal-interval semantics in information retrieval. Within this lattice framework, we design a dynamic programming algorithm that uses the lattice operations of meet and join. To the best of our knowledge, this is the first geometric application of the Clarke-Cormack-Burkowski lattice.

Cite as

Jaehoon Chung. Orthogonal Strip Partitioning of Polygons: Lattice-Theoretic Algorithms and Lower Bounds. In 20th Scandinavian Symposium on Algorithm Theory (SWAT 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 370, pp. 14:1-14:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{chung:LIPIcs.SWAT.2026.14,
  author =	{Chung, Jaehoon},
  title =	{{Orthogonal Strip Partitioning of Polygons: Lattice-Theoretic Algorithms and Lower Bounds}},
  booktitle =	{20th Scandinavian Symposium on Algorithm Theory (SWAT 2026)},
  pages =	{14:1--14:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-421-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{370},
  editor =	{Fraigniaud, Pierre},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SWAT.2026.14},
  URN =		{urn:nbn:de:0030-drops-260506},
  doi =		{10.4230/LIPIcs.SWAT.2026.14},
  annote =	{Keywords: Polygon partitioning, Strip partition, Lattice, Self-overlapping curves}
}

Document

DOI: 10.4230/LIPIcs.ITCS.2026.36

Beyond 2-Edge-Connectivity: Algorithms and Impossibility for Content-Oblivious Leader Election

Authors: Yi-Jun Chang, Lyuting Chen, and Haoran Zhou

Published in: LIPIcs, Volume 362, 17th Innovations in Theoretical Computer Science Conference (ITCS 2026)

Abstract

The content-oblivious model, introduced by Censor-Hillel, Cohen, Gelles, and Sela (PODC 2022; Distributed Computing 2023), captures an extremely weak form of communication where nodes can only send asynchronous, content-less pulses. They showed that in 2-edge-connected networks, any distributed algorithm can be simulated in the content-oblivious model, provided that a unique leader is designated a priori. Subsequent works of Frei, Gelles, Ghazy, and Nolin (DISC 2024) and Chalopin et al. (DISC 2025) developed content-oblivious leader election algorithms, first for unoriented rings and then for general 2-edge-connected graphs. These results establish that all graph problems are solvable in content-oblivious, 2-edge-connected networks. Much less is known about networks that are not 2-edge-connected. Censor-Hillel, Cohen, Gelles, and Sela showed that no non-constant function f(x,y) can be computed correctly by two parties using content-oblivious communication over a single edge, where one party holds x and the other holds y. This seemingly ruled out many natural graph problems on non-2-edge-connected graphs. In this work, we show that, with the knowledge of network topology G, leader election is possible in a wide range of graphs. Our main contributions are as follows: Impossibility: Graphs symmetric about an edge admit no randomized terminating leader election algorithm, even when nodes have unique identifiers and full knowledge of G. Leader election algorithms: Trees that are not symmetric about any edge admit a quiescently terminating leader election algorithm with topology knowledge, even in anonymous networks, using O(n²) messages, where n is the number of nodes. Moreover, even-diameter trees admit a terminating leader election given only the knowledge of the network diameter D = 2r, with message complexity O(nr). Necessity of topology knowledge: In the family of graphs 𝒢 = {P₃, P₅}, both the 3-path P₃ and the 5-path P₅ admit a quiescently terminating leader election if nodes know the topology exactly. However, if nodes only know that the underlying topology belongs to 𝒢, then terminating leader election is impossible.

Cite as

Yi-Jun Chang, Lyuting Chen, and Haoran Zhou. Beyond 2-Edge-Connectivity: Algorithms and Impossibility for Content-Oblivious Leader Election. In 17th Innovations in Theoretical Computer Science Conference (ITCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 362, pp. 36:1-36:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{chang_et_al:LIPIcs.ITCS.2026.36,
  author =	{Chang, Yi-Jun and Chen, Lyuting and Zhou, Haoran},
  title =	{{Beyond 2-Edge-Connectivity: Algorithms and Impossibility for Content-Oblivious Leader Election}},
  booktitle =	{17th Innovations in Theoretical Computer Science Conference (ITCS 2026)},
  pages =	{36:1--36:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-410-9},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{362},
  editor =	{Saraf, Shubhangi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2026.36},
  URN =		{urn:nbn:de:0030-drops-253239},
  doi =		{10.4230/LIPIcs.ITCS.2026.36},
  annote =	{Keywords: Asynchronous model, fault tolerance, quiescent termination}
}

Document

DOI: 10.4230/LIPIcs.ESA.2025.17

Weighted Matching in a Poly-Streaming Model

Authors: Ahammed Ullah, S M Ferdous, and Alex Pothen

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

We introduce the poly-streaming model, a generalization of streaming models of computation in which k processors process k data streams containing a total of N items. The algorithm is allowed 𝒪(f(k)⋅M₁) space, where M₁ is either o (N) or the space bound for a sequential streaming algorithm. Processors may communicate as needed. Algorithms are assessed by the number of passes, per-item processing time, total runtime, space usage, communication cost, and solution quality. We design a single-pass algorithm in this model for approximating the maximum weight matching (MWM) problem. Given k edge streams and a parameter ε > 0, the algorithm computes a (2+ε)-approximate MWM. We analyze its performance in a shared-memory parallel setting: for any constant ε > 0, it runs in time 𝒪̃(L_{max}+n), where n is the number of vertices and L_{max} is the maximum stream length. It supports 𝒪(1) per-edge processing time using 𝒪̃(k⋅n) space. We further generalize the design to hierarchical architectures, in which k processors are partitioned into r groups, each with its own shared local memory. The total intergroup communication is 𝒪̃(r⋅n) bits, while all other performance guarantees are preserved. We evaluate the algorithm on a shared-memory system using graphs with trillions of edges. It achieves substantial speedups as k increases and produces matchings with weights significantly exceeding the theoretical guarantee. On our largest test graph, it reduces runtime by nearly two orders of magnitude and memory usage by five orders of magnitude compared to an offline algorithm.

Cite as

Ahammed Ullah, S M Ferdous, and Alex Pothen. Weighted Matching in a Poly-Streaming Model. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 17:1-17:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ullah_et_al:LIPIcs.ESA.2025.17,
  author =	{Ullah, Ahammed and Ferdous, S M and Pothen, Alex},
  title =	{{Weighted Matching in a Poly-Streaming Model}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{17:1--17:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.17},
  URN =		{urn:nbn:de:0030-drops-244858},
  doi =		{10.4230/LIPIcs.ESA.2025.17},
  annote =	{Keywords: Streaming Algorithms, Matchings, Graphs, Parallel Algorithms}
}

Document

DOI: 10.4230/LIPIcs.ESA.2025.109

Combined Search and Encoding for Seeds, with an Application to Minimal Perfect Hashing

Authors: Hans-Peter Lehmann, Peter Sanders, Stefan Walzer, and Jonatan Ziegler

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

Randomised algorithms often employ methods that can fail and that are retried with independent randomness until they succeed. Randomised data structures therefore often store indices of successful attempts, called seeds. If n such seeds are required (e.g., for independent substructures) the standard approach is to compute for each i ∈ [n] the smallest successful seed S_i and store S = (S_1,…,S_n). The central observation of this paper is that this is not space-optimal. We present a different algorithm that computes a sequence S' = (S_1',…,S_n') of successful seeds such that the entropy of S' undercuts the entropy of S by Ω(n) bits in most cases. To achieve a memory consumption of OPT+εn, the expected number of inspected seeds increases by a factor of 𝒪(1/ε). We demonstrate the usefulness of our findings with a novel construction for minimal perfect hash functions that, for n keys and any ε ∈ [n^{-3/7},1], has space requirement (1+ε)OPT and construction time 𝒪(n/ε). All previous approaches only support ε = ω(1/log n) or have construction times that increase exponentially with 1/ε. Our implementation beats the construction throughput of the state of the art by more than two orders of magnitude for ε ≤ 3%.

Cite as

Hans-Peter Lehmann, Peter Sanders, Stefan Walzer, and Jonatan Ziegler. Combined Search and Encoding for Seeds, with an Application to Minimal Perfect Hashing. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 109:1-109:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lehmann_et_al:LIPIcs.ESA.2025.109,
  author =	{Lehmann, Hans-Peter and Sanders, Peter and Walzer, Stefan and Ziegler, Jonatan},
  title =	{{Combined Search and Encoding for Seeds, with an Application to Minimal Perfect Hashing}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{109:1--109:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.109},
  URN =		{urn:nbn:de:0030-drops-245780},
  doi =		{10.4230/LIPIcs.ESA.2025.109},
  annote =	{Keywords: Random Seed, Encoding, Bernoulli Process, Backtracking, Perfect Hashing}
}

Document

DOI: 10.4230/LIPIcs.ESA.2025.9

MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing

Authors: Stefan Hermann

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

A minimal perfect hash function (MPHF) maps a set of n keys to unique positions {1, …, n}. Representing an MPHF requires at least log₂(e)≈ 1.443 bits per key. ShockHash is a technique to construct an MPHF and requires just slightly more space. It gives each key two random candidate positions. If each key can be mapped to one of its two candidate positions such that there is exactly one key mapped to each position, then an MPHF is found. If not, ShockHash repeats the process with a new set of random candidate positions. ShockHash has to store how many repetitions were required and for each key to which of the two candidate positions it is mapped. However, when a given set of candidate positions can be used as MPHF then there is not only one but multiple ways of mapping the keys to one of their candidate positions such that the mapping results in an MPHF. This redundancy makes up for the majority of the remaining space overhead in ShockHash. In this paper, we present MorphisHash which almost completely eliminates this redundancy. Our theoretical result is that MorphisHash saves Θ(ln(n)) bits in expectation compared to ShockHash. This corresponds to a factor of 20 less space overhead in practice. Just like ShockHash, MorphisHash can be used as a building block within RecSplit to obtain MorphisHash-RS. When compared for same space consumption, MorphisHash-RS can be constructed up to 21 times faster than ShockHash-RS. The technique to accomplish this might be of a more general interest to compress data structures.

Cite as

Stefan Hermann. MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 9:1-9:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hermann:LIPIcs.ESA.2025.9,
  author =	{Hermann, Stefan},
  title =	{{MorphisHash: Improving Space Efficiency of ShockHash for Minimal Perfect Hashing}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{9:1--9:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.9},
  URN =		{urn:nbn:de:0030-drops-244779},
  doi =		{10.4230/LIPIcs.ESA.2025.9},
  annote =	{Keywords: compressed data structure, perfect hashing, random graph, pseudoforest, component}
}

Document

DOI: 10.4230/LIPIcs.ESA.2025.99

Engineering Minimal k-Perfect Hash Functions

Authors: Stefan Hermann, Sebastian Kirmayer, Hans-Peter Lehmann, Peter Sanders, and Stefan Walzer

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

Given a set S of n keys, a k-perfect hash function (kPHF) is a data structure that maps the keys to the first m integers, where each output integer can be hit by at most k input keys. When m = ⌈n/k⌉, the resulting function is called a minimal k-perfect hash function (MkPHF). Applications of kPHFs can be found in external memory data structures or to create efficient 1-perfect hash functions, which in turn have a wide range of applications from databases to bioinformatics. Several papers from the 1980s look at external memory data structures with small internal memory indexes. However, actual k-perfect hash functions are surprisingly rare, and the area has not seen a lot of research recently. At the same time, recent research in 1-perfect hashing shows that there is a lack of efficient kPHFs. In this paper, we revive the area of k-perfect hashing, presenting four new constructions. Our implementations simultaneously dominate older approaches in space consumption, construction time, and query time. We see this paper as a possible starting point of an active line of research, similar to the area of 1-perfect hashing.

Cite as

Stefan Hermann, Sebastian Kirmayer, Hans-Peter Lehmann, Peter Sanders, and Stefan Walzer. Engineering Minimal k-Perfect Hash Functions. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 99:1-99:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{hermann_et_al:LIPIcs.ESA.2025.99,
  author =	{Hermann, Stefan and Kirmayer, Sebastian and Lehmann, Hans-Peter and Sanders, Peter and Walzer, Stefan},
  title =	{{Engineering Minimal k-Perfect Hash Functions}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{99:1--99:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.99},
  URN =		{urn:nbn:de:0030-drops-245685},
  doi =		{10.4230/LIPIcs.ESA.2025.99},
  annote =	{Keywords: Compressed Data Structures, Perfect Hashing}
}

Document

Research

DOI: 10.4230/OASIcs.Grossi.15

Wavelet Tree, Part I: A Brief History

Authors: Paolo Ferragina, Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, Rossano Venturini, and Jeffrey Scott Vitter

Published in: OASIcs, Volume 132, From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday (2025)

Abstract

The Wavelet Tree data structure introduced in Grossi, Gupta, and Vitter [Grossi et al., 2003] is a space-efficient technique for rank and select queries that generalizes from binary symbols to an arbitrary multisymbol alphabet. Over the last two decades, it has become a pivotal tool in modern full-text indexing and data compression because of its properties and capabilities in compressing and indexing data, with many applications to information retrieval, genome analysis, data mining, and web search. In this paper, we survey the fascinating history and impact of Wavelet Trees; no doubt many more developments are yet to come. Our survey borrows some content from the authors' earlier works. This paper is divided into two parts: one (this one) giving a brief history of Wavelet Trees, including its varieties and practical implementations, dedicated to this Festschrift’s honoree Roberto Grossi; the second part deals with Wavelet Tree-based text indexing and is included in the Festschrift dedicated to Giovanni Manzini [Ferragina et al., 2025].

Cite as

Paolo Ferragina, Raffaele Giancarlo, Giovanni Manzini, Giovanna Rosone, Rossano Venturini, and Jeffrey Scott Vitter. Wavelet Tree, Part I: A Brief History. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 15:1-15:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ferragina_et_al:OASIcs.Grossi.15,
  author =	{Ferragina, Paolo and Giancarlo, Raffaele and Manzini, Giovanni and Rosone, Giovanna and Venturini, Rossano and Vitter, Jeffrey Scott},
  title =	{{Wavelet Tree, Part I: A Brief History}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{15:1--15:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.15},
  URN =		{urn:nbn:de:0030-drops-238143},
  doi =		{10.4230/OASIcs.Grossi.15},
  annote =	{Keywords: Wavelet tree, data compression, text indexing, compressed suffix array, Burrows-Wheeler transform, rank and select}
}

@InProceedings{ferragina_et_al:OASIcs.Grossi.15,
  author =	{Ferragina, Paolo and Giancarlo, Raffaele and Manzini, Giovanni and Rosone, Giovanna and Venturini, Rossano and Vitter, Jeffrey Scott},
  title =	{{Wavelet Tree, Part I: A Brief History}},
  booktitle =	{From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday},
  pages =	{15:1--15:11},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-391-1},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{132},
  editor =	{Conte, Alessio and Marino, Andrea and Rosone, Giovanna and Vitter, Jeffrey Scott},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.Grossi.15},
  URN =		{urn:nbn:de:0030-drops-238143},
  doi =		{10.4230/OASIcs.Grossi.15},
  annote =	{Keywords: Wavelet tree, data compression, text indexing, compressed suffix array, Burrows-Wheeler transform, rank and select}
}

Document

DOI: 10.4230/LIPIcs.CP.2025.40

An Efficient and Uniform CSP Solution Generator Generator

Authors: Ghiles Ziat and Martin Pépin

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract

Constraint-based random testing is a powerful technique which aims at generating random test cases to verify functional properties of a program. Its objective is to determine whether a function satisfies a given property for every possible input. This approach requires firstly defining the property to satisfy, then secondly to provide a "generator of inputs" able to feed the program with the inputs generated. Besides, function inputs often need to satisfy certain constraints to ensure the function operates correctly, which makes the crafting of such a generator a hard task. In this paper, we are interested in the problem of manufacturing a uniform and efficient generator for the solutions of a CSP. In order to do that, we propose a specialized solving method that produces a well-suited representation for random sampling. Our solving method employs a dedicated propagation scheme based on the hypergraph representation of a CSP, and a custom split heuristic called birdge-first that emphasizes the interests of our propagation scheme. The generators we build are general enough to handle a wide range of use-cases. They are moreover uniform by construction, iterative and self-improving. We present a prototype built upon the AbSolute constraint solving library and demonstrate its performances on several realistic examples.

Cite as

Ghiles Ziat and Martin Pépin. An Efficient and Uniform CSP Solution Generator Generator. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 40:1-40:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{ziat_et_al:LIPIcs.CP.2025.40,
  author =	{Ziat, Ghiles and P\'{e}pin, Martin},
  title =	{{An Efficient and Uniform CSP Solution Generator Generator}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{40:1--40:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.40},
  URN =		{urn:nbn:de:0030-drops-239010},
  doi =		{10.4230/LIPIcs.CP.2025.40},
  annote =	{Keywords: Constraint Programming, Property-based Testing}
}

Document

DOI: 10.4230/LIPIcs.CP.2025.24

The Work Task Variation Problem

Authors: Mikael Z. Lagerkvist and Magnus Rattfeldt

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract

This paper introduces the Work Task Variation (WTV) problem, a novel scheduling post-processing challenge focused on improving worker shift quality by rearranging tasks within their assigned time slots. The objective is to avoid excessively short or long durations of specific task types, creating smoother and more ergonomic work patterns. We present RosterLogic Variation, a constraint-based local search (CBLS) inspired solver originally developed at Optischedule and successfully deployed in real-world retail settings. This solver rapidly improves existing schedules using tailored invariants and heuristics. We also provide a complete MiniZinc model and a set of generated realistic publicly available benchmark instances. We compare our solver’s performance with that of modern CP solvers using the MiniZinc model. Contemporary state-of-the-art CP solvers are approaching the interactive performance of our CBLS solver for coarse planning, representing a significant advancement since the original design and implementation of our solver.

Cite as

Mikael Z. Lagerkvist and Magnus Rattfeldt. The Work Task Variation Problem. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 24:1-24:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{lagerkvist_et_al:LIPIcs.CP.2025.24,
  author =	{Lagerkvist, Mikael Z. and Rattfeldt, Magnus},
  title =	{{The Work Task Variation Problem}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{24:1--24:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.24},
  URN =		{urn:nbn:de:0030-drops-238850},
  doi =		{10.4230/LIPIcs.CP.2025.24},
  annote =	{Keywords: Constraint-Based Local Search, Constraint Programming, Metaheuristics, Scheduling}
}

Document

DOI: 10.4230/LIPIcs.SEA.2025.21

PtrHash: Minimal Perfect Hashing at RAM Throughput

Authors: Ragnar Groot Koerkamp

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)

Abstract

Motivation. Given a set K of n keys, a minimal perfect hash function (MPHF) is a collision-free bijective map H_mphf from K to {0, … , n-1}. These functions have uses in databases, search engines, and are used in bioinformatics indexing tools such as Pufferfish (using BBHash), and Piscem (PTHash). PTHash is also used in SSHash, a data structure on k-mers that supports membership queries. PTHash only takes around 5% of the total space of SSHash, and thus, trading slightly more space for faster queries is beneficial. Thus, this work presents a (minimal) perfect hash function that first prioritizes query throughput, while also allowing efficient construction for 10⁹ or more elements using 2.4 bits of memory per key. Contributions. Both PTHash and PHOBIC first map all n keys to n/λ < n buckets. Then, each bucket stores a pilot that controls the final hash value of the keys mapping to it. PtrHash builds on this by using 1) fixed-width (uncompressed) 8-bit pilots, 2) a construction algorithm similar to Cuckoo hashing to find suitable pilot values. Further, it partitions the keys, so that keys in each part map to their own set of slots. PtrHash 3) uses the same number of buckets and slots for each part, with 4) a single remap table to map intermediate positions ≥ n to < n, 5) encoded using per-cacheline Elias-Fano coding. Lastly, 6) PtrHash supports streaming queries, where we use prefetching to answer a stream of multiple queries more efficiently than one-by-one processing. Results. With default parameters, PtrHash takes 2.4 bits per key. On 300 million string keys, PtrHash is as fast or faster to build than other MPHFs at a similar size, and at least 2.1× faster to query. When streaming multiple queries, this improves to 3.3× speedup over the fastest alternative, while also being significantly faster to construct. When using 10⁹ integer keys instead, query times are as low as 12 ns/key when iterating in a for loop, or even down to 8 ns/key when using the streaming approach, just short of the 7.4 ns inverse throughput of random memory accesses.

Cite as

Ragnar Groot Koerkamp. PtrHash: Minimal Perfect Hashing at RAM Throughput. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 21:1-21:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{grootkoerkamp:LIPIcs.SEA.2025.21,
  author =	{Groot Koerkamp, Ragnar},
  title =	{{PtrHash: Minimal Perfect Hashing at RAM Throughput}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{21:1--21:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.21},
  URN =		{urn:nbn:de:0030-drops-232597},
  doi =		{10.4230/LIPIcs.SEA.2025.21},
  annote =	{Keywords: Minimal perfect hashing, Compressed Data Structures}
}

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