25 Search Results for "Tan, Tian"


Document
Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper

Authors: Dhruv Meduri, Chuan-Shen Hu, Cong Shen, Kelin Xia, and Bei Wang

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)


Abstract
The vast chemical space, encompassing virtually innumerable molecules and materials, presents both immense opportunities and significant challenges. The design and discovery of novel drugs and functional materials may be viewed as a search within this space; however, the sheer scale of potential candidates renders exhaustive exploration infeasible. To address this, we introduce Chemical Mapper, a framework that integrates topological data analysis with deep learning to enable the visual exploration and analysis of chemical latent spaces. At its core, Chemical Mapper employs mapper, a widely used tool in topological data analysis, to investigate the organizational principles of chemical latent spaces defined by molecular representations learned by geometric deep learning models. In doing so, Chemical Mapper not only highlights groups of molecular representations but also uncovers the relationships among them through linkages and branching structures. Our results show that Chemical Mapper reveals intrinsic patterns associated with molecular scaffolds, functional groups, and chemical properties, as well as the structural and functional evolutions of the molecules.

Cite as

Dhruv Meduri, Chuan-Shen Hu, Cong Shen, Kelin Xia, and Bei Wang. Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 78:1-78:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{meduri_et_al:LIPIcs.SoCG.2026.78,
  author =	{Meduri, Dhruv and Hu, Chuan-Shen and Shen, Cong and Xia, Kelin and Wang, Bei},
  title =	{{Mapping Chemical Space: Topological Data Analysis of Chemical Latent Space with Mapper}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{78:1--78:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.78},
  URN =		{urn:nbn:de:0030-drops-258854},
  doi =		{10.4230/LIPIcs.SoCG.2026.78},
  annote =	{Keywords: Practice of computational topology, topological data analysis, applications in chemistry, mapper algorithm, high-dimensional data analysis, chemical spaces, geometric deep learning, latent space geometry}
}
Document
Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality

Authors: Anup Agarwal, Venkat Arun, and Srinivasan Seshan

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)


Abstract
Congestion control algorithms (CCAs) operate in partially observable environments. They cannot directly observe link capacities or competing flows. To share network resources fairly, CCAs (implicitly) communicate fair shares through observable signals. For instance, Reno encodes the fair share as ∝ 1/√{loss rate}. We call such communication mechanisms as contracts. We find that the choice of contract fixes key steady-state performance metrics, including (1) robustness to errors in congestion signals, (2) fairness, (3) amount of congestion (e.g., delay, loss), and (4) generality (e.g., range of supported link rates). This leads to fundamental tradeoffs between these metrics. Further, we show that many contracts lead to starvation (extreme unfairness), and must be avoided. Hence, contracts are a powerful way to analyze tradeoffs and avoid pitfalls in CCA design and analysis. We empirically validate our findings and discuss their implications on CCA design and network measurement.

Cite as

Anup Agarwal, Venkat Arun, and Srinivasan Seshan. Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 8:1-8:30, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{agarwal_et_al:OASIcs.NINeS.2026.8,
  author =	{Agarwal, Anup and Arun, Venkat and Seshan, Srinivasan},
  title =	{{Contracts: A Unified Lens on Congestion Control Robustness, Fairness, Congestion, and Generality}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{8:1--8:30},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.8},
  URN =		{urn:nbn:de:0030-drops-255933},
  doi =		{10.4230/OASIcs.NINeS.2026.8},
  annote =	{Keywords: Transport Protocols, Congestion Control, Fairness}
}
Document
Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery

Authors: Ziqian Liu, Om Chabra, James Lynch, Aaron Martin, Chenning Li, and Hari Balakrishnan

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)


Abstract
This paper presents CityMesh, a city-scale decentralized mesh network designed for disaster recovery and emergency scenarios. When wide-area Internet connectivity is unavailable or severely degraded, CityMesh leverages both static access points and mobile devices equipped with Wi-Fi to provide intra-city connectivity and reach opportunistic gateways to the Internet (e.g., via satellite links). The main contribution of this paper is a scalable routing protocol that supports millions of devices, addressing a long-standing limitation of wireless mesh and mobile ad hoc networks. Unlike prior approaches, CityMesh exploits rich building-location and building-geometry data from widely available city maps to guide route computation, improving packet delivery while significantly reducing transmission overhead. Simulation results from 70 cities show that CityMesh improves packet delivery rates by 88% over WEAVE (a state-of-the-art geographic routing protocol). A campus-scale deployment of 300 Wi-Fi devices across 31 buildings shows the practical deployability of CityMesh. These results demonstrate the promise of map-aware routing as a foundation for scalable, resilient city-wide Wi-Fi networks.

Cite as

Ziqian Liu, Om Chabra, James Lynch, Aaron Martin, Chenning Li, and Hari Balakrishnan. Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 10:1-10:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{liu_et_al:OASIcs.NINeS.2026.10,
  author =	{Liu, Ziqian and Chabra, Om and Lynch, James and Martin, Aaron and Li, Chenning and Balakrishnan, Hari},
  title =	{{Scalable Routing in a City-Scale Wi-Fi Network for Disaster Recovery}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{10:1--10:31},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.10},
  URN =		{urn:nbn:de:0030-drops-255954},
  doi =		{10.4230/OASIcs.NINeS.2026.10},
  annote =	{Keywords: mesh networking, disaster recovery, geographic routing, scalability, Wi-Fi}
}
Document
BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks

Authors: Jon Larrea, Tanya Shreedhar, Atte Niemi, Adel Sefiane, and Mahesh K. Marina

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)


Abstract
Mobile application performance is often bottlenecked by cellular links with rapid bandwidth fluctuations. We show that radio KPIs from the device chipset can precisely and promptly measure available cellular bandwidth. Building on this, we propose Biscay, a practical KPI-driven congestion control for mobile networks. Biscay leverages OpenDiag, an in-kernel, real-time KPI extractor we introduce along with a KPI-based bandwidth estimator to adjust the congestion window, utilizing available bandwidth while minimizing delay. We implement Biscay and OpenDiag on unrooted Android 5G phones. Across trace-driven emulations and real-world 4G/5G experiments, Biscay outperforms state-of-the-art CCAs (e.g., BBR, CUBIC), typically reducing average and tail delay by >90% while matching or improving throughput. These gains stem from OpenDiag’s 100× finer on-device KPI granularity than existing alternatives like MobileInsight.

Cite as

Jon Larrea, Tanya Shreedhar, Atte Niemi, Adel Sefiane, and Mahesh K. Marina. BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 15:1-15:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{larrea_et_al:OASIcs.NINeS.2026.15,
  author =	{Larrea, Jon and Shreedhar, Tanya and Niemi, Atte and Sefiane, Adel and Marina, Mahesh K.},
  title =	{{BISCAY: Practical Radio KPI Driven Congestion Control for Mobile Networks}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{15:1--15:32},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.15},
  URN =		{urn:nbn:de:0030-drops-256002},
  doi =		{10.4230/OASIcs.NINeS.2026.15},
  annote =	{Keywords: Cellular Networks, Congestion Control, LTE/5G}
}
Document
Simulate Before Sending: Rethinking Transport in Datacenter Networks

Authors: Dan Straussman, Isaac Keslassy, Alexander Shpiner, and Liran Liss

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)


Abstract
Existing transport protocols in commodity datacenter networks struggle to provide low collective completion times (CCTs) to AI training collectives, as packet losses and retransmissions significantly degrade performance. We propose dcSim, an efficient transport that achieves low CCTs and practically lossless performance with commodity switches. In dcSim, each packet first employs a small simulation probe to traverse the network and explore congestion along a candidate path. Only packets whose simulation probes succeed are then transmitted, expecting to succeed as well. Evaluations confirm that dcSim achieves faster CCTs than existing schemes, with small queues and virtually zero packet loss. Finally, dcSim also excels in adverse conditions, including oversubscribed topologies.

Cite as

Dan Straussman, Isaac Keslassy, Alexander Shpiner, and Liran Liss. Simulate Before Sending: Rethinking Transport in Datacenter Networks. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 19:1-19:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{straussman_et_al:OASIcs.NINeS.2026.19,
  author =	{Straussman, Dan and Keslassy, Isaac and Shpiner, Alexander and Liss, Liran},
  title =	{{Simulate Before Sending: Rethinking Transport in Datacenter Networks}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{19:1--19:22},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.19},
  URN =		{urn:nbn:de:0030-drops-256044},
  doi =		{10.4230/OASIcs.NINeS.2026.19},
  annote =	{Keywords: Datacenter networks, transport protocols, AI training, lossless networks}
}
Document
Performance Isolation for 5G RAN Slices Across Multiple Interfering Cells

Authors: Taimoor Tariq, Yongzhou Chen, Haitham Hassanieh, and Radhika Mittal

Published in: OASIcs, Volume 139, 1st New Ideas in Networked Systems (NINeS 2026)


Abstract
Radio Access Network (RAN) slicing, a key 5G feature, enables different slices (i.e. tenants or applications) to share the same physical network infrastructure while pursuing diverse objectives such as fairness, prioritization, or maximizing throughput. Each slice is allocated a share of radio resource blocks (RBs), which it further schedules among its users as per its own performance objective. In this paper, we identify the unique challenges that arise when performing RAN slicing in today’s multi-cell deployments that require a mechanism for managing interference among cells. We highlight how interference management decisions, that can be easily made in the absence of slicing (where all users share a common objective set by the network operator), become challenging with 5G slicing where we must respect the individual objectives of multiple slices, while retaining performance isolation across slices. We present a system, RadioNinja, that tackles this challenge through a unique decision-making framework that allows different slices to independently contribute towards interference management decisions. RadioNinja further employs a series of techniques to make such decisions within tight RAN scheduling budget of hundreds of microseconds. Trace-driven simulations with real-world channel measurements show that RadioNinja improves slice-level objectives (e.g., throughput, fairness, flow completion times) by 20–60% over state-of-the-art baselines, while consistently meeting sub-millisecond decision deadlines.

Cite as

Taimoor Tariq, Yongzhou Chen, Haitham Hassanieh, and Radhika Mittal. Performance Isolation for 5G RAN Slices Across Multiple Interfering Cells. In 1st New Ideas in Networked Systems (NINeS 2026). Open Access Series in Informatics (OASIcs), Volume 139, pp. 2:1-2:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


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@InProceedings{tariq_et_al:OASIcs.NINeS.2026.2,
  author =	{Tariq, Taimoor and Chen, Yongzhou and Hassanieh, Haitham and Mittal, Radhika},
  title =	{{Performance Isolation for 5G RAN Slices Across Multiple Interfering Cells}},
  booktitle =	{1st New Ideas in Networked Systems (NINeS 2026)},
  pages =	{2:1--2:29},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-414-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{139},
  editor =	{Argyraki, Katerina and Panda, Aurojit},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.NINeS.2026.2},
  URN =		{urn:nbn:de:0030-drops-255875},
  doi =		{10.4230/OASIcs.NINeS.2026.2},
  annote =	{Keywords: Cellular Networks, Resource Management, RAN Slicing, Interference Management}
}
Document
Research
Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web

Authors: Florian Ruosch, Cristina Sarasua, and Abraham Bernstein

Published in: TGDK, Volume 3, Issue 3 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 3


Abstract
In Argument Mining, predicting argumentative relations between texts (or spans) remains one of the most challenging aspects, even more so in the cross-document setting. This paper makes three key contributions to advance research in this domain. We first extend an existing dataset, the Sci-Arg corpus, by annotating it with explicit inter-document argumentative relations, thereby allowing arguments to be distributed over several documents forming an Argument Web; these new annotations are published using Semantic Web technologies (RDF, OWL). Second, we explore and evaluate three automated approaches for predicting these inter-document argumentative relations, establishing critical baselines on the new dataset. We find that a simple classifier based on discourse indicators with access to context outperforms neural methods. Third, we conduct a comparative analysis of these approaches for both intra- and inter-document settings, identifying statistically significant differences in results that indicate the necessity of distinguishing between these two scenarios. Our findings highlight significant challenges in this complex domain and open crucial avenues for future research on the Argument Web of Science, particularly for those interested in leveraging Semantic Web technologies and knowledge graphs to understand scholarly discourse. With this, we provide the first stepping stones in the form of a benchmark dataset, three baseline methods, and an initial analysis for a systematic exploration of this field relevant to the Web of Data and Science.

Cite as

Florian Ruosch, Cristina Sarasua, and Abraham Bernstein. Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 3, pp. 4:1-4:33, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@Article{ruosch_et_al:TGDK.3.3.4,
  author =	{Ruosch, Florian and Sarasua, Cristina and Bernstein, Abraham},
  title =	{{Mining Inter-Document Argument Structures in Scientific Papers for an Argument Web}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:33},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{3},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.3.4},
  URN =		{urn:nbn:de:0030-drops-252159},
  doi =		{10.4230/TGDK.3.3.4},
  annote =	{Keywords: Argument Mining, Large Language Models, Knowledge Graphs, Link Prediction}
}
Document
Survey
Resilience in Knowledge Graph Embeddings

Authors: Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo

Published in: TGDK, Volume 3, Issue 2 (2025). Transactions on Graph Data and Knowledge, Volume 3, Issue 2


Abstract
In recent years, knowledge graphs have gained interest and witnessed widespread applications in various domains, such as information retrieval, question-answering, recommendation systems, amongst others. Large-scale knowledge graphs to this end have demonstrated their utility in effectively representing structured knowledge. To further facilitate the application of machine learning techniques, knowledge graph embedding models have been developed. Such models can transform entities and relationships within knowledge graphs into vectors. However, these embedding models often face challenges related to noise, missing information, distribution shift, adversarial attacks, etc. This can lead to sub-optimal embeddings and incorrect inferences, thereby negatively impacting downstream applications. While the existing literature has focused so far on adversarial attacks on KGE models, the challenges related to the other critical aspects remain unexplored. In this paper, we, first of all, give a unified definition of resilience, encompassing several factors such as generalisation, in-distribution generalization, distribution adaption, and robustness. After formalizing these concepts for machine learning in general, we define them in the context of knowledge graphs. To find the gap in the existing works on resilience in the context of knowledge graphs, we perform a systematic survey, taking into account all these aspects mentioned previously. Our survey results show that most of the existing works focus on a specific aspect of resilience, namely robustness. After categorizing such works based on their respective aspects of resilience, we discuss the challenges and future research directions.

Cite as

Arnab Sharma, N'Dah Jean Kouagou, and Axel-Cyrille Ngonga Ngomo. Resilience in Knowledge Graph Embeddings. In Transactions on Graph Data and Knowledge (TGDK), Volume 3, Issue 2, pp. 1:1-1:38, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@Article{sharma_et_al:TGDK.3.2.1,
  author =	{Sharma, Arnab and Kouagou, N'Dah Jean and Ngomo, Axel-Cyrille Ngonga},
  title =	{{Resilience in Knowledge Graph Embeddings}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{1:1--1:38},
  ISSN =	{2942-7517},
  year =	{2025},
  volume =	{3},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.3.2.1},
  URN =		{urn:nbn:de:0030-drops-248117},
  doi =		{10.4230/TGDK.3.2.1},
  annote =	{Keywords: Knowledge graphs, Resilience, Robustness}
}
Document
DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs

Authors: Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall

Published in: LIPIcs, Volume 344, 25th International Conference on Algorithms for Bioinformatics (WABI 2025)


Abstract
Determining the distance between two loci within a genomic region is a recurrent operation in various tasks in computational genomics. A notable example of this task arises in paired-end read mapping as a form of validation of distances between multiple alignments. While straightforward for a single genome, graph-based reference structures render the operation considerably more involved. Given the sheer number of such queries in a typical read mapping experiment, an efficient algorithm for answering distance queries is crucial. In this paper, we introduce DiVerG, a compact data structure as well as a fast and scalable algorithm, for constructing distance indexes for general sequence graphs on multi-core CPU and many-core GPU architectures. DiVerG is based on PairG [Jain et al., 2019], but overcomes the limitations of PairG by exploiting the extensive potential for improvements in terms of scalability and space efficiency. As a consequence, DiVerG can process substantially larger datasets, such as whole human genomes, which are unmanageable by PairG. DiVerG offers faster index construction time and consistently faster query time with gains proportional to the size of the underlying compact data structure. We demonstrate that our method performs favorably on multiple real datasets at various scales. DiVerG achieves superior performance over PairG; e.g. resulting to 2.5-4x speed-up in query time, 44-340x smaller index size, and 3-50x faster construction time for the genome graph of the MHC region, as a particularly variable region of the human genome. The implementation is available at: https://github.com/cartoonist/diverg

Cite as

Ali Ghaffaari, Alexander Schönhuth, and Tobias Marschall. DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs. In 25th International Conference on Algorithms for Bioinformatics (WABI 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 344, pp. 10:1-10:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{ghaffaari_et_al:LIPIcs.WABI.2025.10,
  author =	{Ghaffaari, Ali and Sch\"{o}nhuth, Alexander and Marschall, Tobias},
  title =	{{DiVerG: Scalable Distance Index for Validation of Paired-End Alignments in Sequence Graphs}},
  booktitle =	{25th International Conference on Algorithms for Bioinformatics (WABI 2025)},
  pages =	{10:1--10:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-386-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{344},
  editor =	{Brejov\'{a}, Bro\v{n}a and Patro, Rob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2025.10},
  URN =		{urn:nbn:de:0030-drops-239369},
  doi =		{10.4230/LIPIcs.WABI.2025.10},
  annote =	{Keywords: Sequence graph, distance index, read mapping, sparse matrix}
}
Document
LoRaHART: Hardware-Aware Real-Time Scheduling for LoRa

Authors: Soumya Ranjan Sahoo, Amalinda Gamage, Niraj Kumar, and Arvind Easwaran

Published in: LIPIcs, Volume 335, 37th Euromicro Conference on Real-Time Systems (ECRTS 2025)


Abstract
Time-sensitive data acquisition is critical for many Low-Power Wide-Area Network (LPWAN) applications, such as healthcare monitoring and industrial Internet of Things. Among the available LPWAN technologies, LoRa (Long Range) has emerged as a leading choice, offering kilometer-scale communication with minimal power consumption and enabling high-density deployments across large areas. However, the conventional ALOHA-based Medium Access Control (MAC) in LoRa is not designed to support real-time communication over large-scale networks. This paper introduces LoRaHART, a novel approach that overcomes two critical, under-explored limitations in Commercial Off The Shelf (COTS) LoRa gateways that impact real-time performance. LoRa gateways have limited capacity for demodulation of parallel transmissions and their antenna can either transmit or receive at any time instant. LoRaHART incorporates a hardware-aware super-frame structure, comprising both Time Division Multiple Access (TDMA) slots as well as opportunistic retransmissions using Carrier Sense Multiple Access (CSMA), designed to mitigate the above constraints. We use a partial packing and makespan minimization algorithm to schedule periodic real-time transmissions efficiently within the TDMA slots, and also develop a probabilistic node contention model for CSMA retransmissions, providing analytical guarantees for deadline satisfaction under ideal channel conditions. Our evaluation of LoRaHART on a 40-node LoRa testbed demonstrates significant improvements over existing solutions in practice, achieving an average Packet Reception Ratio of 98% and a 45% higher airtime utilization than the best performing baseline.

Cite as

Soumya Ranjan Sahoo, Amalinda Gamage, Niraj Kumar, and Arvind Easwaran. LoRaHART: Hardware-Aware Real-Time Scheduling for LoRa. In 37th Euromicro Conference on Real-Time Systems (ECRTS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 335, pp. 10:1-10:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{sahoo_et_al:LIPIcs.ECRTS.2025.10,
  author =	{Sahoo, Soumya Ranjan and Gamage, Amalinda and Kumar, Niraj and Easwaran, Arvind},
  title =	{{LoRaHART: Hardware-Aware Real-Time Scheduling for LoRa}},
  booktitle =	{37th Euromicro Conference on Real-Time Systems (ECRTS 2025)},
  pages =	{10:1--10:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-377-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{335},
  editor =	{Mancuso, Renato},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2025.10},
  URN =		{urn:nbn:de:0030-drops-235880},
  doi =		{10.4230/LIPIcs.ECRTS.2025.10},
  annote =	{Keywords: LoRa, LPWAN, Real-time Scheduling, Hardware Constraints}
}
Document
Track A: Algorithms, Complexity and Games
k-Leaf Powers Cannot Be Characterized by a Finite Set of Forbidden Induced Subgraphs for k ≥ 5

Authors: Max Dupré la Tour, Manuel Lafond, Ndiamé Ndiaye, and Adrian Vetta

Published in: LIPIcs, Volume 334, 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)


Abstract
A graph G = (V,E) is a k-leaf power if there is a tree T whose leaves are the vertices of G, with the property that a pair of distinct leaves u and v share an edge in G if and only if they are distance at most k apart in T. For k ≤ 4, it is known that there exists a finite set F_k of graphs such that the class ℒ(k) of k-leaf power graphs is characterized as the set of strongly chordal graphs that do not contain any graph in F_k as an induced subgraph. We prove no such characterization holds for k ≥ 5. That is, for any k ≥ 5, there is no finite set F_k of graphs such that ℒ(k) is equivalent to the set of strongly chordal graphs that do not contain as an induced subgraph any graph in F_k.

Cite as

Max Dupré la Tour, Manuel Lafond, Ndiamé Ndiaye, and Adrian Vetta. k-Leaf Powers Cannot Be Characterized by a Finite Set of Forbidden Induced Subgraphs for k ≥ 5. In 52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 334, pp. 72:1-72:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{duprelatour_et_al:LIPIcs.ICALP.2025.72,
  author =	{Dupr\'{e} la Tour, Max and Lafond, Manuel and Ndiaye, Ndiam\'{e} and Vetta, Adrian},
  title =	{{k-Leaf Powers Cannot Be Characterized by a Finite Set of Forbidden Induced Subgraphs for k ≥ 5}},
  booktitle =	{52nd International Colloquium on Automata, Languages, and Programming (ICALP 2025)},
  pages =	{72:1--72:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-372-0},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{334},
  editor =	{Censor-Hillel, Keren and Grandoni, Fabrizio and Ouaknine, Jo\"{e}l and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2025.72},
  URN =		{urn:nbn:de:0030-drops-234499},
  doi =		{10.4230/LIPIcs.ICALP.2025.72},
  annote =	{Keywords: Leaf Powers, Forbidden Graph Characterizations, Strongly Chordal Graphs}
}
Document
Chain of Grounded Objectives: Concise Goal-Oriented Prompting for Code Generation

Authors: Sangyeop Yeo, Seung-Won Hwang, and Yu-Seung Ma

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)


Abstract
The use of Large Language Models (LLMs) for code generation has gained significant attention in recent years. Existing methods often aim to improve the quality of generated code by incorporating additional contextual information or guidance into input prompts. Many of these approaches adopt process-oriented reasoning strategies, mimicking human-like step-by-step thinking; however, they may not always align with the structured nature of programming languages. This paper introduces Chain of Grounded Objectives (CGO), a concise goal-oriented prompting approach that embeds functional objectives into prompts to enhance code generation. By focusing on precisely defined objectives rather than explicit procedural steps, CGO aligns more naturally with programming tasks while retaining flexibility. Empirical evaluations on HumanEval, MBPP, their extended versions, and LiveCodeBench show that CGO achieves accuracy comparable to or better than existing methods while using fewer tokens, making it a more efficient approach to LLM-based code generation.

Cite as

Sangyeop Yeo, Seung-Won Hwang, and Yu-Seung Ma. Chain of Grounded Objectives: Concise Goal-Oriented Prompting for Code Generation. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 35:1-35:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{yeo_et_al:LIPIcs.ECOOP.2025.35,
  author =	{Yeo, Sangyeop and Hwang, Seung-Won and Ma, Yu-Seung},
  title =	{{Chain of Grounded Objectives: Concise Goal-Oriented Prompting for Code Generation}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{35:1--35:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.35},
  URN =		{urn:nbn:de:0030-drops-233271},
  doi =		{10.4230/LIPIcs.ECOOP.2025.35},
  annote =	{Keywords: Artificial Intelligence, Natural Language Processing, Prompt Design, Large Language Models, Code Generation}
}
Document
FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation

Authors: Amber Gorzynski and Alastair F. Donaldson

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)


Abstract
Decompilation is the process of translating compiled code into high-level code. Control flow recovery is a challenging part of the process. "Misdecompilations" can occur, whereby the decompiled code does not accurately represent the semantics of the compiled code, despite it being syntactically valid. This is problematic because it can mislead users who are trying to reason about the program. We present CFG-based program generation: a novel approach to randomised testing that aims to improve the control flow recovery of decompilers. CFG-based program generation involves randomly generating control flow graphs (CFGs) and paths through each graph. Inspired by prior work in the domain of GPU computing, (CFG, path) pairs are "fleshed" into test programs. Each program is decompiled and recompiled. The test oracle verifies whether the actual runtime path through the graph matches the expected path. Any difference in the execution paths after recompilation indicates a possible misdecompilation. A key benefit of this approach is that it is largely independent of the source and target languages in question because it is focused on control flow. The approach is therefore applicable to numerous decompilation settings. The trade-off resulting from the focus on control flow is that misdecompilation bugs that do not relate to control flow (e.g. bugs that involve specific arithmetic operations) are out of scope. We have implemented this approach in FuzzFlesh, an open-source randomised testing tool. FuzzFlesh can be easily configured to target a variety of low-level languages and decompiler toolchains because most of the CFG and path generation process is language-independent. At present, FuzzFlesh supports testing decompilation of Java bytecode, .NET assembly and x86 machine code. In addition to program generation, FuzzFlesh also includes an automated test-case reducer that operates on the CFG rather than the low-level program, which means that it can be applied to any of the target languages. We present a large experimental campaign applying FuzzFlesh to a variety of decompilers, leading to the discovery of 12 previously-unknown bugs across two language formats, six of which have been fixed. We present experiments comparing our generic FuzzFlesh tool to two state-of-the-art decompiler testing tools targeted at specific languages. As expected, the coverage our generic FuzzFlesh tool achieves on a given decompiler is lower than the coverage achieved by a tool specifically designed for the input format of that decompiler. However, due to its focus on control flow, FuzzFlesh is able to cover sections of control flow recovery code that the targeted tools cannot reach, and identify control flow related bugs that the targeted tools miss.

Cite as

Amber Gorzynski and Alastair F. Donaldson. FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 13:1-13:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{gorzynski_et_al:LIPIcs.ECOOP.2025.13,
  author =	{Gorzynski, Amber and Donaldson, Alastair F.},
  title =	{{FuzzFlesh: Randomised Testing of Decompilers via Control Flow Graph-Based Program Generation}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{13:1--13:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.13},
  URN =		{urn:nbn:de:0030-drops-233062},
  doi =		{10.4230/LIPIcs.ECOOP.2025.13},
  annote =	{Keywords: Decompiler, Reverse Engineering, Control Flow, Software Testing, Fuzzing}
}
Document
Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories

Authors: Tianyu Chen, Zeyu Wang, Lin Li, Ding Li, Zongyang Li, Xiaoning Chang, Pan Bian, Guangtai Liang, Qianxiang Wang, and Tao Xie

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)


Abstract
Functionality-specific vulnerabilities, which mainly occur in Application Programming Interfaces (APIs) with specific functionalities, are crucial for software developers to detect and avoid. When detecting individual functionality-specific vulnerabilities, the existing two categories of approaches are ineffective because they consider only the API bodies and are unable to handle diverse implementations of functionality-equivalent APIs. To effectively detect functionality-specific vulnerabilities, we propose APISS, the first approach to utilize API doc strings and signatures instead of API bodies. APISS first retrieves functionality-equivalent APIs for APIs with existing vulnerabilities and then migrates Proof-of-Concepts (PoCs) of the existing vulnerabilities for newly detected vulnerable APIs. To retrieve functionality-equivalent APIs, we leverage a Large Language Model for API embedding to improve the accuracy and address the effectiveness and scalability issues suffered by the existing approaches. To migrate PoCs of the existing vulnerabilities for newly detected vulnerable APIs, we design a semi-automatic schema to substantially reduce manual costs. We conduct a comprehensive evaluation to empirically compare APISS with four state-of-the-art approaches of detecting vulnerabilities and two state-of-the-art approaches of retrieving functionality-equivalent APIs. The evaluation subjects include 180 widely used Java repositories using 10 existing vulnerabilities, along with their PoCs. The results show that APISS effectively retrieves functionality-equivalent APIs, achieving a Top-1 Accuracy of 0.81 while the best of the baselines under comparison achieves only 0.55. APISS is highly efficient: the manual costs are within 10 minutes per vulnerability and the end-to-end runtime overhead of testing one candidate API is less than 2 hours. APISS detects 179 new vulnerabilities and receives 60 new CVE IDs, bringing high value to security practice.

Cite as

Tianyu Chen, Zeyu Wang, Lin Li, Ding Li, Zongyang Li, Xiaoning Chang, Pan Bian, Guangtai Liang, Qianxiang Wang, and Tao Xie. Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 6:1-6:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{chen_et_al:LIPIcs.ECOOP.2025.6,
  author =	{Chen, Tianyu and Wang, Zeyu and Li, Lin and Li, Ding and Li, Zongyang and Chang, Xiaoning and Bian, Pan and Liang, Guangtai and Wang, Qianxiang and Xie, Tao},
  title =	{{Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{6:1--6:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.6},
  URN =		{urn:nbn:de:0030-drops-232999},
  doi =		{10.4230/LIPIcs.ECOOP.2025.6},
  annote =	{Keywords: Application Security, Vulnerability Detection, Large Language Model}
}
Document
Profile-Guided Field Externalization in an Ahead-Of-Time Compiler

Authors: Sebastian Kloibhofer, Lukas Makor, Peter Hofer, David Leopoldseder, and Hanspeter Mössenböck

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)


Abstract
Field externalization is a technique to reduce the footprint of objects by removing fields that most frequently contain zero or null. While researchers have developed ways to bring this optimization into the Java world, these have been limited to research compilers or virtual machines for embedded systems. In this work, we present a novel field externalization technique that uses information from static analysis and profiling to determine externalizable fields. During compilation, we remove those fields and define companion classes. These are used in case of non-default-value writes to the externalized fields. Our approach also correctly handles synchronization to prevent issues in multithreaded environments. We integrated our approach into the modern Java ahead-of-time compiler GraalVM Native Image. We conducted an evaluation on a diverse set of benchmarks that includes standard and microservice-based benchmarks. For standard benchmarks, our approach reduces the total allocated bytes by 2.76% and the maximum resident set size (max-RSS) by 2.55%. For microservice benchmarks, we achieved a reduction of 6.88% for normalized allocated bytes and 2.45% for max-RSS. We computed these improvements via the geometric mean. The median reductions are are 1.46% (alloc. bytes) and 0.22% (max-RSS) in standard benchmarks, as well as 3.63% (alloc. bytes) and 0.20% (max-RSS) in microservice benchmarks.

Cite as

Sebastian Kloibhofer, Lukas Makor, Peter Hofer, David Leopoldseder, and Hanspeter Mössenböck. Profile-Guided Field Externalization in an Ahead-Of-Time Compiler. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 19:1-19:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{kloibhofer_et_al:LIPIcs.ECOOP.2025.19,
  author =	{Kloibhofer, Sebastian and Makor, Lukas and Hofer, Peter and Leopoldseder, David and M\"{o}ssenb\"{o}ck, Hanspeter},
  title =	{{Profile-Guided Field Externalization in an Ahead-Of-Time Compiler}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{19:1--19:32},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.19},
  URN =		{urn:nbn:de:0030-drops-233121},
  doi =		{10.4230/LIPIcs.ECOOP.2025.19},
  annote =	{Keywords: compilation, instrumentation, profiling, fields, externalization, memory footprint reduction, memory footprint optimization}
}
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