37 Search Results for "Zheng, Yu"

Document
DOI: 10.4230/OASIcs.ATMOS.2024.2
Indexing Graphs for Shortest Beer Path Queries

Authors: David Coudert, Andrea D'Ascenzo, and Mattia D'Emidio

Published in: OASIcs, Volume 123, 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024)

Abstract
A beer graph is an edge-weighted graph G = (V,E,ω) with beer vertices B ⊆ V. A beer path between two vertices s and t of a beer graph is a path that connects s and t and visits at least one vertex in B. The beer distance between two vertices is the weight of a shortest beer path, i.e. a beer path having minimum total weight. A graph indexing scheme is a two-phase method that constructs an index data structure by a one-time preprocessing of an input graph and then exploits it to compute (or accelerate the computation of) answers to queries on structures of the graph dataset. In the last decade, such indexing schemes have been designed to perform, effectively, many relevant types of queries, e.g. on reachability, and have gained significant popularity in essentially all data-intensive application domains where large number of queries have to be routinely answered (e.g. journey planners), since they have been shown, through many experimental studies, to offer extremely low query times at the price of limited preprocessing time and space overheads. In this paper, we showcase that an indexing scheme, to efficiently execute queries on beer distances or shortest beer paths for pairs of vertices of a beer graph, can be obtained by adapting the highway labeling, a recently introduced indexing method to accelerate the computation of classical shortest paths. We design a preprocessing algorithm to build a whl index, i.e. a weighted highway labeling of a beer graph, and show how it can be queried to compute beer distances and shortest beer paths. Through extensive experimentation on real networks, we empirically demonstrate its practical effectiveness and superiority, in terms of offered trade-off between preprocessing time, space overhead and query time, with respect to the state-of-the-art.
Cite as

David Coudert, Andrea D'Ascenzo, and Mattia D'Emidio. Indexing Graphs for Shortest Beer Path Queries. In 24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024). Open Access Series in Informatics (OASIcs), Volume 123, pp. 2:1-2:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{coudert_et_al:OASIcs.ATMOS.2024.2,
  author =	{Coudert, David and D'Ascenzo, Andrea and D'Emidio, Mattia},
  title =	{{Indexing Graphs for Shortest Beer Path Queries}},
  booktitle =	{24th Symposium on Algorithmic Approaches for Transportation Modelling, Optimization, and Systems (ATMOS 2024)},
  pages =	{2:1--2:18},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-350-8},
  ISSN =	{2190-6807},
  year =	{2024},
  volume =	{123},
  editor =	{Bouman, Paul C. and Kontogiannis, Spyros C.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ATMOS.2024.2},
  URN =		{urn:nbn:de:0030-drops-211907},
  doi =		{10.4230/OASIcs.ATMOS.2024.2},
  annote =	{Keywords: Graph Algorithms, Indexing Schemes, Beer Distances, Algorithms Engineering}
}
Document
DOI: 10.4230/LIPIcs.ESA.2024.58
Random-Order Online Independent Set of Intervals and Hyperrectangles

Authors: Mohit Garg, Debajyoti Kar, and Arindam Khan

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
In the Maximum Independent Set of Hyperrectangles problem, we are given a set of n (possibly overlapping) d-dimensional axis-aligned hyperrectangles, and the goal is to find a subset of non-overlapping hyperrectangles of maximum cardinality. For d = 1, this corresponds to the classical Interval Scheduling problem, where a simple greedy algorithm returns an optimal solution. In the offline setting, for d-dimensional hyperrectangles, polynomial time (log n)^{O(d)}-approximation algorithms are known [Chalermsook and Chuzhoy, 2009]. However, the problem becomes notably challenging in the online setting, where the input objects (hyperrectangles) appear one by one in an adversarial order, and on the arrival of an object, the algorithm needs to make an immediate and irrevocable decision whether or not to select the object while maintaining the feasibility. Even for interval scheduling, an Ω(n) lower bound is known on the competitive ratio. To circumvent these negative results, in this work, we study the online maximum independent set of axis-aligned hyperrectangles in the random-order arrival model, where the adversary specifies the set of input objects which then arrive in a uniformly random order. Starting from the prototypical secretary problem, the random-order model has received significant attention to study algorithms beyond the worst-case competitive analysis (see the survey by Gupta and Singla [Anupam Gupta and Sahil Singla, 2020]). Surprisingly, we show that the problem in the random-order model almost matches the best-known offline approximation guarantees, up to polylogarithmic factors. In particular, we give a simple (log n)^{O(d)}-competitive algorithm for d-dimensional hyperrectangles in this model, which runs in O_d̃(n) time. Our approach also yields (log n)^{O(d)}-competitive algorithms in the random-order model for more general objects such as d-dimensional fat objects and ellipsoids. Furthermore, all our competitiveness guarantees hold with high probability, and not just in expectation.
Cite as

Mohit Garg, Debajyoti Kar, and Arindam Khan. Random-Order Online Independent Set of Intervals and Hyperrectangles. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 58:1-58:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{garg_et_al:LIPIcs.ESA.2024.58,
  author =	{Garg, Mohit and Kar, Debajyoti and Khan, Arindam},
  title =	{{Random-Order Online Independent Set of Intervals and Hyperrectangles}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{58:1--58:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John 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.2024.58},
  URN =		{urn:nbn:de:0030-drops-211298},
  doi =		{10.4230/LIPIcs.ESA.2024.58},
  annote =	{Keywords: Online Algorithms, Random-Order Model, Maximum Independent Set of Rectangles, Hyperrectangles, Fat Objects, Interval Scheduling}
}
Document
APPROX
DOI: 10.4230/LIPIcs.APPROX/RANDOM.2024.9
On the Generalized Mean Densest Subgraph Problem: Complexity and Algorithms

Authors: Karthekeyan Chandrasekaran, Chandra Chekuri, Manuel R. Torres, and Weihao Zhu

Published in: LIPIcs, Volume 317, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)

Abstract
Dense subgraph discovery is an important problem in graph mining and network analysis with several applications. Two canonical polynomial-time solvable problems here are to find a maxcore (subgraph of maximum min degree) and to find a densest subgraph (subgraph of maximum average degree). Both of these problems can be solved in polynomial time. Veldt, Benson, and Kleinberg [Veldt et al., 2021] introduced the generalized p-mean densest subgraph problem which captures the maxcore problem when p = -∞ and the densest subgraph problem when p = 1. They observed that for p ≥ 1, the objective function is supermodular and hence the problem can be solved in polynomial time. In this work, we focus on the p-mean densest subgraph problem for p ∈ (-∞, 1). We prove that for every p ∈ (-∞,1), the problem is NP-hard, thus resolving an open question from [Veldt et al., 2021]. We also show that for every p ∈ (0,1), the weighted version of the problem is APX-hard. On the algorithmic front, we describe two simple 1/2-approximation algorithms for every p ∈ (-∞, 1). We complement the approximation algorithms by exhibiting non-trivial instances on which the algorithms simultaneously achieve an approximation factor of at most 1/2.
Cite as

Karthekeyan Chandrasekaran, Chandra Chekuri, Manuel R. Torres, and Weihao Zhu. On the Generalized Mean Densest Subgraph Problem: Complexity and Algorithms. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 9:1-9:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{chandrasekaran_et_al:LIPIcs.APPROX/RANDOM.2024.9,
  author =	{Chandrasekaran, Karthekeyan and Chekuri, Chandra and Torres, Manuel R. and Zhu, Weihao},
  title =	{{On the Generalized Mean Densest Subgraph Problem: Complexity and Algorithms}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{9:1--9:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-348-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{317},
  editor =	{Kumar, Amit and Ron-Zewi, Noga},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2024.9},
  URN =		{urn:nbn:de:0030-drops-210025},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.9},
  annote =	{Keywords: Densest subgraph problem, Hardness of approximation, Approximation algorithms}
}
Document
DOI: 10.4230/LIPIcs.AFT.2024.4
Cross Ledger Transaction Consistency for Financial Auditing

Authors: Vlasis Koutsos, Xiangan Tian, Dimitrios Papadopoulos, and Dimitris Chatzopoulos

Published in: LIPIcs, Volume 316, 6th Conference on Advances in Financial Technologies (AFT 2024)

Abstract
Auditing throughout a fiscal year is integral to organizations with transactional activity. Organizations transact with each other and record the details for all their economical activities so that a regulatory committee can verify the lawfulness and legitimacy of their activity. However, it is computationally infeasible for the committee to perform all necessary checks for each organization. To overcome this, auditors assist in this process: organizations give access to all their internal data to their auditors, who then produce reports regarding the consistency of the organization’s data, alerting the committee to any inconsistencies. Despite this, numerous issues that result in fines annually revolve around such inconsistencies in bookkeeping across organizations. Notably, committees wishing to verify the correctness of auditor-provided reports need to redo all their calculations; a process which is computationally proportional to the number of organizations. In fact, it becomes prohibitive when considering real-world settings with thousands of organizations. In this work, we propose two protocols, CLOSC and CLOLC, whose goals are to enable auditors and a committee to verify the consistency of transactions across different ledgers. Both protocols ensure that for every transaction recorded in an organization’s ledger, there exists a dual one in the ledger of another organization while safeguarding against other potential attacks. Importantly, we minimize the information leakage to auditors and other organizations and guarantee three crucial security and privacy properties that we propose: (i) transaction amount privacy, (ii) organization-auditor unlinkability, and (iii) transacting organizations unlinkability. At the core of our protocols lies a two-tier ledger architecture alongside a suite of cryptographic tools. To demonstrate the practicality and scalability of our designs, we provide extensive performance evaluation for both CLOSC and CLOLC. Our numbers are promising, i.e., all computation and verification times lie in the range of seconds, even for millions of transactions, while the on-chain storage costs for an auditing epoch are encouraging i.e. in the range of GB for millions of transactions and thousands of organizations.
Cite as

Vlasis Koutsos, Xiangan Tian, Dimitrios Papadopoulos, and Dimitris Chatzopoulos. Cross Ledger Transaction Consistency for Financial Auditing. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 4:1-4:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{koutsos_et_al:LIPIcs.AFT.2024.4,
  author =	{Koutsos, Vlasis and Tian, Xiangan and Papadopoulos, Dimitrios and Chatzopoulos, Dimitris},
  title =	{{Cross Ledger Transaction Consistency for Financial Auditing}},
  booktitle =	{6th Conference on Advances in Financial Technologies (AFT 2024)},
  pages =	{4:1--4:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-345-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{316},
  editor =	{B\"{o}hme, Rainer and Kiffer, Lucianna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2024.4},
  URN =		{urn:nbn:de:0030-drops-209409},
  doi =		{10.4230/LIPIcs.AFT.2024.4},
  annote =	{Keywords: Financial auditing, Two-tier ledger architecture, Smart contracts, Transaction privacy, Financial entity unlinkability}
}
Document
DOI: 10.4230/LIPIcs.AFT.2024.7
DeFiAligner: Leveraging Symbolic Analysis and Large Language Models for Inconsistency Detection in Decentralized Finance

Authors: Rundong Gan, Liyi Zhou, Le Wang, Kaihua Qin, and Xiaodong Lin

Published in: LIPIcs, Volume 316, 6th Conference on Advances in Financial Technologies (AFT 2024)

Abstract
Decentralized Finance (DeFi) has witnessed a monumental surge, reaching 53.039 billion USD in total value locked. As this sector continues to expand, ensuring the reliability of DeFi smart contracts becomes increasingly crucial. While some users are adept at reading code or the compiled bytecode to understand smart contracts, many rely on documentation. Therefore, discrepancies between the documentation and the deployed code can pose significant risks, whether these discrepancies are due to errors or intentional fraud. To tackle these challenges, we developed DeFiAligner, an end-to-end system to identify inconsistencies between documentation and smart contracts. DeFiAligner incorporates a symbolic execution tool, SEVM, which explores execution paths of on-chain binary code, recording memory and stack states. It automatically generates symbolic expressions for token balance changes and branch conditions, which, along with related project documents, are processed by LLMs. Using structured prompts, the LLMs evaluate the alignment between the symbolic expressions and the documentation. Our tests across three distinct scenarios demonstrate DeFiAligner’s capability to automate inconsistency detection in DeFi, achieving recall rates of 92% and 90% on two public datasets respectively.
Cite as

Rundong Gan, Liyi Zhou, Le Wang, Kaihua Qin, and Xiaodong Lin. DeFiAligner: Leveraging Symbolic Analysis and Large Language Models for Inconsistency Detection in Decentralized Finance. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 7:1-7:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{gan_et_al:LIPIcs.AFT.2024.7,
  author =	{Gan, Rundong and Zhou, Liyi and Wang, Le and Qin, Kaihua and Lin, Xiaodong},
  title =	{{DeFiAligner: Leveraging Symbolic Analysis and Large Language Models for Inconsistency Detection in Decentralized Finance}},
  booktitle =	{6th Conference on Advances in Financial Technologies (AFT 2024)},
  pages =	{7:1--7:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-345-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{316},
  editor =	{B\"{o}hme, Rainer and Kiffer, Lucianna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2024.7},
  URN =		{urn:nbn:de:0030-drops-209431},
  doi =		{10.4230/LIPIcs.AFT.2024.7},
  annote =	{Keywords: Decentralized Finance Security, Large Language Models, Project Review, Symbolic Analysis, Smart Contracts}
}
Document
DOI: 10.4230/LIPIcs.AFT.2024.15
Privacy Comparison for Bitcoin Light Client Implementations

Authors: Arad Kotzer and Ori Rottenstreich

Published in: LIPIcs, Volume 316, 6th Conference on Advances in Financial Technologies (AFT 2024)

Abstract
Light clients implement a simple solution for Bitcoin’s scalability problem, as they do not store the entire blockchain but only the state of particular addresses of interest. To be able to keep track of the updated state of their addresses, light clients rely on full nodes to provide them with the required information. To do so, they must reveal information about the addresses they are interested in. This paper studies the two most common light client implementations, SPV and Neutrino with regards to their privacy. We define privacy metrics for comparing the privacy of the different implementations. We evaluate and compare the privacy of the implementations over time on real Bitcoin data and discuss the inherent privacy-communication tradeoff. In addition, we propose general techniques to enhance light client privacy in the existing implementations. Finally, we propose a new SPV-based light client model, the aggregation model, evaluate it, and show it can achieve enhanced privacy than in the existing light client implementations.
Cite as

Arad Kotzer and Ori Rottenstreich. Privacy Comparison for Bitcoin Light Client Implementations. In 6th Conference on Advances in Financial Technologies (AFT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 316, pp. 15:1-15:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{kotzer_et_al:LIPIcs.AFT.2024.15,
  author =	{Kotzer, Arad and Rottenstreich, Ori},
  title =	{{Privacy Comparison for Bitcoin Light Client Implementations}},
  booktitle =	{6th Conference on Advances in Financial Technologies (AFT 2024)},
  pages =	{15:1--15:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-345-4},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{316},
  editor =	{B\"{o}hme, Rainer and Kiffer, Lucianna},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.AFT.2024.15},
  URN =		{urn:nbn:de:0030-drops-209510},
  doi =		{10.4230/LIPIcs.AFT.2024.15},
  annote =	{Keywords: Blockchain, Privacy, Light Clients, Bloom filter}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.15
Rose: Composable Autodiff for the Interactive Web

Authors: Sam Estep, Wode Ni, Raven Rothkopf, and Joshua Sunshine

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Reverse-mode automatic differentiation (autodiff) has been popularized by deep learning, but its ability to compute gradients is also valuable for interactive use cases such as bidirectional computer-aided design, embedded physics simulations, visualizing causal inference, and more. Unfortunately, the web is ill-served by existing autodiff frameworks, which use autodiff strategies that perform poorly on dynamic scalar programs, and pull in heavy dependencies that would result in unacceptable webpage sizes. This work introduces Rose, a lightweight autodiff framework for the web using a new hybrid approach to reverse-mode autodiff, blending conventional tracing and transformation techniques in a way that uses the host language for metaprogramming while also allowing the programmer to explicitly define reusable functions that comprise a larger differentiable computation. We demonstrate the value of the Rose design by porting two differentiable physics simulations, and evaluate its performance on an optimization-based diagramming application, showing Rose outperforming the state-of-the-art in web-based autodiff by multiple orders of magnitude.
Cite as

Sam Estep, Wode Ni, Raven Rothkopf, and Joshua Sunshine. Rose: Composable Autodiff for the Interactive Web. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 15:1-15:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{estep_et_al:LIPIcs.ECOOP.2024.15,
  author =	{Estep, Sam and Ni, Wode and Rothkopf, Raven and Sunshine, Joshua},
  title =	{{Rose: Composable Autodiff for the Interactive Web}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{15:1--15:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.15},
  URN =		{urn:nbn:de:0030-drops-208642},
  doi =		{10.4230/LIPIcs.ECOOP.2024.15},
  annote =	{Keywords: Automatic differentiation, differentiable programming, compilers, web}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.18
A CFL-Reachability Formulation of Callsite-Sensitive Pointer Analysis with Built-In On-The-Fly Call Graph Construction

Authors: Dongjie He, Jingbo Lu, and Jingling Xue

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
In object-oriented languages, the traditional CFL-reachability formulation for k-callsite-sensitive pointer analysis (kCFA) focuses on modeling field accesses and calling contexts, but it relies on a separate algorithm for call graph construction. This division can result in a loss of precision in kCFA, a problem that persists even when using the most precise call graphs, whether pre-constructed or generated on the fly. Moreover, pre-analyses based on this framework aiming to improve the efficiency of kCFA may inadvertently reduce its precision, due to the framework’s lack of native call graph construction, essential for precise analysis. Addressing this gap, this paper introduces a novel CFL-reachability formulation of kCFA for Java, uniquely integrating on-the-fly call graph construction. This advancement not only addresses the precision loss inherent in the traditional CFL-reachability-based approach but also enhances its overall applicability. In a significant secondary contribution, we present the first precision-preserving pre-analysis to accelerate kCFA. This pre-analysis leverages selective context sensitivity to improve the efficiency of kCFA without sacrificing its precision. Collectively, these contributions represent a substantial step forward in pointer analysis, offering both theoretical and practical advancements that could benefit future developments in the field.
Cite as

Dongjie He, Jingbo Lu, and Jingling Xue. A CFL-Reachability Formulation of Callsite-Sensitive Pointer Analysis with Built-In On-The-Fly Call Graph Construction. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 18:1-18:29, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{he_et_al:LIPIcs.ECOOP.2024.18,
  author =	{He, Dongjie and Lu, Jingbo and Xue, Jingling},
  title =	{{A CFL-Reachability Formulation of Callsite-Sensitive Pointer Analysis with Built-In On-The-Fly Call Graph Construction}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{18:1--18:29},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.18},
  URN =		{urn:nbn:de:0030-drops-208674},
  doi =		{10.4230/LIPIcs.ECOOP.2024.18},
  annote =	{Keywords: Pointer Analysis, CFL Reachability, Call Graph Construction}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.20
Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization

Authors: Florian Huemer, David Leopoldseder, Aleksandar Prokopec, Raphael Mosaner, and Hanspeter Mössenböck

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Improving compilation time in optimizing compilers is challenging due to their large number of interconnected components. This includes compiler optimizations, compiler tiers, heuristics, and profiling information. Despite this complexity, research in compilation-time optimization is often guided by analyzing metrics of entire program runs, such as the total compilation time and overall memory footprint. This coarse-grained perspective hides relevant information, such as source program functions for which the compiler allocates a lot of memory or compiler optimizations with a high impact on the total compilation time. This leaves high-level metrics as the only reference point for driving optimization design. Consequently, compilation-time regressions in one program function that are obscured by improvements in other functions stay undetected, while the impacts of compiler changes on untouched parts of the compiler are mainly unknown. Furthermore, developers overlook long-standing compiler defects because their high-level metrics do not change over time. To address these limitations, we propose ICON, a new data-driven approach to compilation-time optimization that breaks up high-level metrics into individual source program functions, compiler optimizations, or even into individual instructions in the compiler source code. Our methodology enables an iterative in-depth compilation-time analysis, focusing on outliers to identify optimization opportunities. We show that outliers, both in terms of time spent in a particular compiler optimization, and in terms of individual compilations that take substantially longer, can reveal potential problems in the compiler implementation. We applied our approach to GraalVM and extracted data for multiple of its language runtimes. We analyzed the resulting data, present the first detailed look into the distribution of compilation time in the GraalVM compiler, a state-of-the-art multi-language compiler, and identified defects that led to regressions in overall compilation time or the compilation time of specific languages. We furthermore designed two optimizations based on the identified outliers that improve compilation time between 2.25% and 9.45%. We believe that our approach can guide compiler developers in finding usually overlooked optimization potential and defects, and focus future research efforts in making compilers more efficient.
Cite as

Florian Huemer, David Leopoldseder, Aleksandar Prokopec, Raphael Mosaner, and Hanspeter Mössenböck. Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 20:1-20:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{huemer_et_al:LIPIcs.ECOOP.2024.20,
  author =	{Huemer, Florian and Leopoldseder, David and Prokopec, Aleksandar and Mosaner, Raphael and M\"{o}ssenb\"{o}ck, Hanspeter},
  title =	{{Taking a Closer Look: An Outlier-Driven Approach to Compilation-Time Optimization}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{20:1--20:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.20},
  URN =		{urn:nbn:de:0030-drops-208693},
  doi =		{10.4230/LIPIcs.ECOOP.2024.20},
  annote =	{Keywords: Compilation time, outliers, dynamic languages, virtual machines, GraalVM, ICON}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.21
Learning Gradual Typing Performance

Authors: Mohammad Wahiduzzaman Khan, Sheng Chen, and Yi He

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Gradual typing has emerged as a promising typing discipline for reconciling static and dynamic typing, which have respective strengths and shortcomings. Thanks to its promises, gradual typing has gained tremendous momentum in both industry and academia. A main challenge in gradual typing is that, however, the performance of its programs can often be unpredictable, and adding or removing the type of a a single parameter may lead to wild performance swings. Many approaches have been proposed to optimize gradual typing performance, but little work has been done to aid the understanding of the performance landscape of gradual typing and navigating the migration process (which adds type annotations to make programs more static) to avert performance slowdowns. Motivated by this situation, this work develops a machine-learning-based approach to predict the performance of each possible way of adding type annotations to a program. On top of that, many supports for program migrations could be developed, such as finding the most performant neighbor of any given configuration. Our approach gauges runtime overheads of dynamic type checks inserted by gradual typing and uses that information to train a machine learning model, which is used to predict the running time of gradual programs. We have evaluated our approach on 12 Python benchmarks for both guarded and transient semantics. For guarded semantics, our evaluation results indicate that with only 40 training instances generated from each benchmark, the predicted times for all other instances differ on average by 4% from the measured times. For transient semantics, the time difference ratio is higher but the time difference is often within 0.1 seconds.
Cite as

Mohammad Wahiduzzaman Khan, Sheng Chen, and Yi He. Learning Gradual Typing Performance. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 21:1-21:27, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{khan_et_al:LIPIcs.ECOOP.2024.21,
  author =	{Khan, Mohammad Wahiduzzaman and Chen, Sheng and He, Yi},
  title =	{{Learning Gradual Typing Performance}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{21:1--21:27},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.21},
  URN =		{urn:nbn:de:0030-drops-208706},
  doi =		{10.4230/LIPIcs.ECOOP.2024.21},
  annote =	{Keywords: Gradual typing performance, type migration, performance prediction, machine learning}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.29
Generalizing Shape Analysis with Gradual Types

Authors: Zeina Migeed, James Reed, Jason Ansel, and Jens Palsberg

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Tensors are multi-dimensional data structures that can represent the data processed by machine learning tasks. Tensor programs tend to be short and readable, and they can leverage libraries and frameworks such as TensorFlow and PyTorch, as well as modern hardware such as GPUs and TPUs. However, tensor programs also tend to obscure shape information, which can cause shape errors that are difficult to find. Such shape errors can be avoided by a combination of shape annotations and shape analysis, but such annotations are burdensome to come up with manually. In this paper, we use gradual typing to reduce the barrier of entry. Gradual typing offers a way to incrementally introduce type annotations into programs. From there, we focus on tool support for type migration, which is a concept that closely models code-annotation tasks and allows us to do shape reasoning and utilize it for different purposes. We develop a comprehensive gradual typing theory to reason about tensor shapes. We then ask three fundamental questions about a gradually typed tensor program. (1) Does the program have a static migration? (2) Given a program and some arithmetic constraints on shapes, can we migrate the program according to the constraints? (3) Can we eliminate branches that depend on shapes? We develop novel tools to address the three problems. For the third problem, there are currently two PyTorch tools that aim to eliminate branches. They do so by eliminating them for just a single input. Our tool is the first to eliminate branches for an infinite class of inputs, using static shape information. Our tools help prevent bugs, alleviate the burden on the programmer of annotating the program, and improves the process of program transformation.
Cite as

Zeina Migeed, James Reed, Jason Ansel, and Jens Palsberg. Generalizing Shape Analysis with Gradual Types. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 29:1-29:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{migeed_et_al:LIPIcs.ECOOP.2024.29,
  author =	{Migeed, Zeina and Reed, James and Ansel, Jason and Palsberg, Jens},
  title =	{{Generalizing Shape Analysis with Gradual Types}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{29:1--29:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.29},
  URN =		{urn:nbn:de:0030-drops-208786},
  doi =		{10.4230/LIPIcs.ECOOP.2024.29},
  annote =	{Keywords: Tensor Shapes, Gradual Types, Migration}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.32
Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations

Authors: Jie Qiu, Colin Cai, Sahil Bhatia, Niranjan Hasabnis, Sanjit A. Seshia, and Alvin Cheung

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Tensor processing infrastructures such as deep learning frameworks and specialized hardware accelerators have revolutionized how computationally intensive code from domains such as deep learning and image processing is executed and optimized. These infrastructures provide powerful and expressive abstractions while ensuring high performance. However, to utilize them, code must be written specifically using the APIs / ISAs of such software frameworks or hardware accelerators. Importantly, given the fast pace of innovation in these domains, code written today quickly becomes legacy as new frameworks and accelerators are developed, and migrating such legacy code manually is a considerable effort. To enable developers in leveraging such DSLs while preserving their current programming paradigm, we present Tenspiler, a verified-lifting-based compiler that uses program synthesis to translate sequential programs written in general-purpose programming languages (e.g., C++ or Python code that does not leverage any specialized framework or accelerator) into tensor operations. Central to Tenspiler is our carefully crafted yet simple intermediate language, named TensIR, that expresses tensor operations. TensIR enables efficient lifting, verification, and code generation. Unlike classical pattern-matching-based compilers, Tenspiler uses program synthesis to translate input code into TensIR, which is then compiled to the target API / ISA. Currently, Tenspiler already supports six DSLs, spanning a broad spectrum of software and hardware environments. Furthermore, we show that new backends can be easily supported by Tenspiler by adding simple pattern-matching rules for TensIR. Using 10 real-world code benchmark suites, our experimental evaluation shows that by translating code to be executed on 6 different software frameworks and hardware devices, Tenspiler offers on average 105× kernel and 9.65× end-to-end execution time improvement over the fully-optimized sequential implementation of the same benchmarks.
Cite as

Jie Qiu, Colin Cai, Sahil Bhatia, Niranjan Hasabnis, Sanjit A. Seshia, and Alvin Cheung. Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 32:1-32:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{qiu_et_al:LIPIcs.ECOOP.2024.32,
  author =	{Qiu, Jie and Cai, Colin and Bhatia, Sahil and Hasabnis, Niranjan and Seshia, Sanjit A. and Cheung, Alvin},
  title =	{{Tenspiler: A Verified-Lifting-Based Compiler for Tensor Operations}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{32:1--32:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.32},
  URN =		{urn:nbn:de:0030-drops-208817},
  doi =		{10.4230/LIPIcs.ECOOP.2024.32},
  annote =	{Keywords: Program Synthesis, Code Transpilation, Tensor DSLs, Verification}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2024.36
Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report

Authors: Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Interprocedural data-flow analysis is important for computing precise information on whole programs. In theory, the popular algorithmic framework interprocedural distributive environments (IDE) provides a tool to solve distributive interprocedural data-flow problems efficiently. Yet, unfortunately, available state-of-the-art implementations of the IDE framework start to run into scalability issues for programs with several thousands of lines of code, depending on the static analysis domain. Since the IDE framework is a basic building block for many static program analyses, this presents a serious limitation. In this paper, we report on our experience with making the IDE algorithm scale to C/C++ applications with up to 500 000 lines of code. We analyze the IDE algorithm and its state-of-the-art implementations to identify their weaknesses related to scalability at both a conceptual and implementation level. Based on this analysis, we propose several optimizations to overcome these weaknesses, aiming at a sweet spot between reducing running time and memory consumption. As a result, we provide an improved IDE solver that implements our optimizations within the PhASAR static analysis framework. Our evaluation on real-world C/C++ applications shows that applying the optimizations speeds up the analysis on average by up to 7×, while also reducing memory consumption by 7× on average as well. For the first time, these optimizations allow us to analyze programs with several hundreds of thousands of lines of LLVM-IR code in reasonable time and space.
Cite as

Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden. Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 36:1-36:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{schiebel_et_al:LIPIcs.ECOOP.2024.36,
  author =	{Schiebel, Fabian and Sattler, Florian and Schubert, Philipp Dominik and Apel, Sven and Bodden, Eric},
  title =	{{Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{36:1--36:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.36},
  URN =		{urn:nbn:de:0030-drops-208859},
  doi =		{10.4230/LIPIcs.ECOOP.2024.36},
  annote =	{Keywords: Interprocedural data-flow analysis, IDE, LLVM, C/C++}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.25
Towards Statistically Significant Taxonomy Aware Co-Location Pattern Detection (Short Paper)

Authors: Subhankar Ghosh, Arun Sharma, Jayant Gupta, and Shashi Shekhar

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Given a collection of Boolean spatial feature types, their instances, a neighborhood relation (e.g., proximity), and a hierarchical taxonomy of the feature types, the goal is to find the subsets of feature types or their parents whose spatial interaction is statistically significant. This problem is for taxonomy-reliant applications such as ecology (e.g., finding new symbiotic relationships across the food chain), spatial pathology (e.g., immunotherapy for cancer), retail, etc. The problem is computationally challenging due to the exponential number of candidate co-location patterns generated by the taxonomy. Most approaches for co-location pattern detection overlook the hierarchical relationships among spatial features, and the statistical significance of the detected patterns is not always considered, leading to potential false discoveries. This paper introduces two methods for incorporating taxonomies and assessing the statistical significance of co-location patterns. The baseline approach iteratively checks the significance of co-locations between leaf nodes or their ancestors in the taxonomy. Using the Benjamini-Hochberg procedure, an advanced approach is proposed to control the false discovery rate. This approach effectively reduces the risk of false discoveries while maintaining the power to detect true co-location patterns. Experimental evaluation and case study results show the effectiveness of the approach.
Cite as

Subhankar Ghosh, Arun Sharma, Jayant Gupta, and Shashi Shekhar. Towards Statistically Significant Taxonomy Aware Co-Location Pattern Detection (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 25:1-25:11, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{ghosh_et_al:LIPIcs.COSIT.2024.25,
  author =	{Ghosh, Subhankar and Sharma, Arun and Gupta, Jayant and Shekhar, Shashi},
  title =	{{Towards Statistically Significant Taxonomy Aware Co-Location Pattern Detection}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{25:1--25:11},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.25},
  URN =		{urn:nbn:de:0030-drops-208404},
  doi =		{10.4230/LIPIcs.COSIT.2024.25},
  annote =	{Keywords: Co-location patterns, spatial data mining, taxonomy, hierarchy, statistical significance, false discovery rate, family-wise error rate}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.COSIT.2024.31
Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts (Short Paper)

Authors: Majid Hojati and Rob Feick

Published in: LIPIcs, Volume 315, 16th International Conference on Spatial Information Theory (COSIT 2024)

Abstract
Interest in applying Large Language Models (LLMs), which use natural language processing (NLP) to provide human-like responses to text-based questions, to geospatial tasks has grown rapidly. Research shows that LLMs can help generate software code and answer some types of geographic questions to varying degrees even without fine-tuning. However, further research is required to explore the types of spatial questions they answer correctly, their abilities to apply spatial reasoning, and the variability between models. In this paper we examine the ability of four LLM models (GPT3.5 and 4, LLAma2.0, Falcon40B) to answer spatial questions that range from basic calculations to more advanced geographic concepts. The intent of this comparison is twofold. First, we demonstrate an extensible method for evaluating LLM’s limitations to supporting spatial data science through correct calculations and code generation. Relatedly, we also consider how these models can aid geospatial learning by providing text-based explanations of spatial concepts and operations. Our research shows common strengths in more basic types of questions, and mixed results for questions relating to more advanced spatial concepts. These results provide insights that may be used to inform strategies for testing and fine-tuning these models to increase their understanding of key spatial concepts.
Cite as

Majid Hojati and Rob Feick. Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts (Short Paper). In 16th International Conference on Spatial Information Theory (COSIT 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 315, pp. 31:1-31:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{hojati_et_al:LIPIcs.COSIT.2024.31,
  author =	{Hojati, Majid and Feick, Rob},
  title =	{{Large Language Models: Testing Their Capabilities to Understand and Explain Spatial Concepts}},
  booktitle =	{16th International Conference on Spatial Information Theory (COSIT 2024)},
  pages =	{31:1--31:9},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-330-0},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{315},
  editor =	{Adams, Benjamin and Griffin, Amy L. and Scheider, Simon and McKenzie, Grant},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.COSIT.2024.31},
  URN =		{urn:nbn:de:0030-drops-208460},
  doi =		{10.4230/LIPIcs.COSIT.2024.31},
  annote =	{Keywords: Geospatial concepts, Large Language Models, LLM, GPT, Llama, Falcon}
}
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