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46th IEEE/ACM International Conference on software Engineering, ICSE 2024

作者： Guo, Yuqi Zhu, Shihao Cai, Yan He, Liang Zhang, Jian State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China TCA Institute of Software Chinese Academy of Sciences University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798400702174

Due to the non-determinism of thread interleaving, predicting concurrency bugs has long been an extremely difficult task. Recently, several sound bug-detecting approaches were proposed. These approaches are based on local search, i.e., mutating the sequential order of the observed trace and predicting whether the mutated sequential order can trigger a bug. Surprisingly, during this process, they never consider reordering the data flow of the pointers, which can be the key point to detecting many complex bugs. To alleviate this weakness, we propose a new flow-sensitive point-to analysis technique ConPTA to help actively reorder the pointer flow during the sequential order mutation process. Based on ConPTA, we further propose a new sound predictive bug-detecting approach Eagle to predict four types of concurrency bugs. They are null pointer dereference (NPD), uninitialized pointer use (UPU), use after free (UAF), and double free (DF). By actively reordering the pointer flow, Eagle can explore a larger search space of the thread interleaving during the mutation and thus detect more concurrency bugs. Our evaluation of Eagle on 10 real-world multi-threaded programs shows that Eagle significantly outperforms four state-of-the-art bug-detecting approaches UFO, ConVul, ConVulPOE and Period in both effectiveness and efficiency. © 2024 IEEE computer Society. All rights reserved.

关键词： Forecasting

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FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph Neural Network 27

FL-GNN: Efficient Fusion of Fuzzy Neural Network and Graph N...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Du, Boyu Zhou, Jingya Liu, Ling She, Xiaolong School of Computer Science and Technology Soochow University China Engineering Lab.of Big Data and Intelligence of Jiangsu Province Soochow University China State Key Lab.for Novel Software Technology Nanjing University China School of Computer Science Georgia Institute of Technology United States

ISBN: (纸本)9781643685489

Graph Neural Networks (GNNs) have become an important graph feature learning paradigm that is extensively applied to graph inference ***, GNNs still have limitations in some aspects such as representation capability, interpretability, *** this end, this paper introduces a novel hybrid Fuzzy-Logic Graph Neural Network (FL-GNN) that synergistically combines Fuzzy Neural Network (FNN) and GNN to effectively capture and aggregate local information flows within the ***-GNN exhibits three distinctive ***, we incorporate a specialized structure fuzzy rule to enhance FL-GNN's graph inference capability, surpassing representative GNN ***, we augment the interpretability of FL-GNN by integrating analytical exploration methods from two perspectives: Fuzzy Inference System and Message Passing Algorithm (MPA).Lastly, we refine the structure of FL-GNN based on MPA to optimize its calculation complexity and consequently improve learning *** results show that FL-GNN outperforms existing representative graph neural networks for graph inference tasks. © 2024 The Authors.

关键词： Graph neural networks

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Collision-resistant hash-shuffles on the reals

arXiv

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arXiv 2025年

作者： Barmpalias, George Zhang, Xiaoyan State Key Lab of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

Oneway real functions are effective maps on positive-measure sets of reals that preserve randomness and have no effective probabilistic inversions. We construct a oneway real function which is collision-resistant: the probability of effectively producing distinct reals with the same image is zero, and each real has uncountable inverse image. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

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Dynamic ocean inverse modeling based on differentiable rendering

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Computational Visual Media 2024年第2期10卷 279-294页

作者： Xueguang Xie Yang Gao Fei Hou Aimin Hao Hong Qin State Key Lab of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Qingdao Research Institute Beihang UniversityQingdao 266100Chinaand Peng Cheng LabShenzhen 518000China SKLCS Institute of SoftwareChinese Academy of SciencesBeijing 100190Chinaand University of Chinese Academy of SciencesBeijing 100049China Department of Computer Science Stony Brook University(SUNY at Stony Brook)Stony BrookNew York 11794-2424USA

Learning and inferring underlying motion patterns of captured 2D scenes and then re-creating dynamic evolution consistent with the real-world natural phenomena have high appeal for graphics and *** bridge the technical gap between virtual and real environments,we focus on the inverse modeling and reconstruction of visually consistent and property-verifiable oceans,taking advantage of deep learning and differentiable physics to learn geometry and constitute waves in a self-supervised ***,we infer hierarchical geometry using two networks,which are optimized via the differentiable *** extract wave components from the sequence of inferred geometry through a network equipped with a differentiable ocean ***,ocean dynamics can be evolved using the reconstructed wave *** extensive experiments,we verify that our new method yields satisfactory results for both geometry reconstruction and wave ***,the new framework has the inverse modeling potential to facilitate a host of graphics applications,such as the rapid production of physically accurate scene animation and editing guided by real ocean scenes.

关键词： inverse modeling surface reconstruction wave modeling ocean waves differentiable rendering(DR)

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Local Search For SMT On Linear and Multi-linear Real Arithmetic 23

Local Search For SMT On Linear and Multi-linear Real Arithme...

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23rd International Conference on Formal Methods in computer-Aided Design, FMCAD 2023

作者： Li, Bohan Cai, Shaowei Institute of Software Chinese Academy of Sciences State Key Laboratory of Computer Science Beijing China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing China

ISBN: (纸本)9783854480600

Satisfiability Modulo Theories (SMT) has significant application in various domains. In this paper, we focus on quantifier-free Satisfiablity Modulo Real Arithmetic, referred to as SMT(RA), including both linear and non-linear real arithmetic theories. As for non-linear real arithmetic theory, we focus on one of its important fragments where the atomic constraints are multi-linear. We propose the first local search algorithm for SMT(RA), called LocalSMT(RA), based on two novel ideas. First, an interval-based operator is proposed to cooperate with the traditional local search operator by considering the interval information. Moreover, we propose a tie-breaking mechanism to further evaluate the operations when the operations are indistinguishable according to the score function. Experiments are conducted to evaluate LocalSMT(RA) on benchmarks from SMT-LIB. The results show that LocalSMT(RA) is competitive with the state-of-the-art SMT solvers, and performs particularly well on multi-linear instances. © 2023 FMCAD Association and individual authors.

关键词： Local search (optimization)

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Crowd2: Multi-agent Bandit-based Dispatch for Video Analytics upon Crowdsourcing 42

Crowd2: Multi-agent Bandit-based Dispatch for Video Analytic...

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42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Chen, Yu Zhang, Sheng Yan, Yuting Jin, Yibo Chen, Ning Ji, Mingtao Xiao, Mingjun Nanjing University State Key Lab. for Novel Software Technology China University of Science and Technology of China School of Computer Science and Technology China

ISBN: (纸本)9798350334142

Many crowdsourcing platforms are emerging, leveraging the resources of recruited workers to execute various outsourcing tasks, mainly for those computing-intensive video analytics with high quality requirements. Although the profit of each platform is strongly related to the quality of analytics feedback, due to the uncertainty on diverse performance of workers and the conflicts of interest over platforms, it is non-trivial to determine the dispatch of tasks with maximum benefits. In this paper, we design a decentralized mechanism for a Crowd of Crowdsourcing platforms, denoted as Crowd2, optimizing the worker selection to maximize the social welfare of these platforms in a long-term scope, under the consideration of both proportional fairness and dynamic flexibility. Concretely, we propose a video analytics dispatch algorithm based on multi-agent bandit, for which the more accurate profit estimates are attained via the decoupling of multi-knapsack based mapping problem. Via rigorous proofs, a sub-linear regret bound for social welfare of crowdsourcing profits is achieved while both fairness and flexibility are ensured. Extensive trace-driven experiments demonstrate that Crowd2 improves the social welfare by 36.8%, compared with other alternatives. © 2023 IEEE.

关键词： Profitability

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Understanding Transaction Bugs in Database Systems 24

Understanding Transaction Bugs in Database Systems

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44th ACM/IEEE International Conference on software Engineering, ICSE 2024

作者： Cui, Ziyu Dou, Wensheng Gao, Yu Wang, Dong Song, Jiansen Zheng, Yingying Wang, Tao Yang, Rui Xu, Kang Hu, Yixin Wei, Jun Huang, Tao State Key Lab of Computer Science at Iscas China University of Cas Beijing China Nanjing Institute of Software Technology China University of Cas Nanjing China Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798400702174

Transactions are used to guarantee data consistency and integrity in Database Management Systems (DBMSs), and have become an indispensable component in DBMSs. However, faulty designs and implementations of DBMSs' transaction processing mechanisms can introduce transaction bugs, and lead to severe consequences, e.g., incorrect database states and DBMS crashes. An in-depth understanding of real-world transaction bugs can significantly promote effective techniques in combating transaction bugs in DBMSs. In this paper, we conduct the first comprehensive study on 140 transaction bugs collected from six widely-used DBMSs, i.e., MySQL, PostgreSQL, SQLite, MariaDB, CockroachDB, and TiDB. We investigate these bugs from their bug manifestations, root causes, bug impacts and bug fixing. Our study reveals many in-teresting findings and provides useful guidance for transaction bug detection, testing, and verification. © 2024 ACM.

关键词： Database systems

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Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 58-73页

作者： Qingsong Zhao Lei Shu Kailiang Li Mohamed Amine Ferrag Ximeng Liu Yanbin Li the College of Artificial Intelligence Nanjing Agricultural UniversityNanjing 210031 the State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023 the State Key Laboratory of Cryptology Beijing 100878China IEEE the School of Engineering University of LincolnLincoln LN67TSUK the Artificial Intelligence and Digital Science Research Center Technology Innovation InstituteMasdar City 9639UAE the College of Computer and Data Science Fuzhou UniversityFuzhou 350108China

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security *** issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

关键词： Challenges Internet of Things(IoT) privacy and security security requirements solar insecticidal lamps(SIL)

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Meta-Cognitive Analysis: Evaluating Declarative and Procedural Knowledge in Datasets and Large Language Models 30

Meta-Cognitive Analysis: Evaluating Declarative and Procedur...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Li, Zhuoqun Lin, Hongyu Lu, Yaojie Xiang, Hao Han, Xianpei Sun, Le Chinese Information Processing Laboratory Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9782493814104

Declarative knowledge and procedural knowledge are two key parts in meta-cognitive theory, and these two hold significant importance in pre-training and inference of LLMs. However, a comprehensive analysis comparing these two types of knowledge is lacking, primarily due to challenges in definition, probing and quantitative assessment. In this paper, we explore from a new perspective by providing ground-truth knowledge for LLMs and evaluating the effective score. Through extensive experiments with widely-used datasets and models, we get conclusions: (1) In most tasks, benefits from declarative knowledge are greater than those from procedural knowledge. (2) Profits of procedural knowledge are larger than declarative knowledge only in reasoning tasks with simple logic. (3) As pre-training progresses and size increases, model ability to utilize both kinds of knowledge significantly improves, but in different speed. We do detailed analysis for the findings and this can provide primary guidance for evaluation and enhancement of large language models. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Large datasets

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SOFTENED SYMBOL GROUNDING FOR NEUROSYMBOLIC SYSTEMS 11

SOFTENED SYMBOL GROUNDING FOR NEUROSYMBOLIC SYSTEMS

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11th International Conference on Learning Representations, ICLR 2023

作者： Li, Zenan Yao, Yuan Chen, Taolue Xu, Jingwei Cao, Chun Ma, Xiaoxing Lü, Jian State Key Lab of Novel Software Technology Nanjing University China Department of Computer Science Birkbeck University of London United Kingdom

Neuro-symbolic learning generally consists of two separated worlds, i.e., neural network training and symbolic constraint solving, whose success hinges on symbol grounding, a fundamental problem in *** paper presents a novel, softened symbol grounding process, bridging the gap between the two worlds, and resulting in an effective and efficient neuro-symbolic learning ***, the framework features (1) modeling of symbol solution states as a Boltzmann distribution, which avoids expensive state searching and facilitates mutually beneficial interactions between network training and symbolic reasoning;(2) a new MCMC technique leveraging projection and SMT solvers, which efficiently samples from disconnected symbol solution spaces;(3) an annealing mechanism that can escape from sub-optimal symbol *** with three representative neuro-symbolic learning tasks demonstrate that, owing to its superior symbol grounding capability, our framework successfully solves problems well beyond the frontier of the existing proposals. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Boltzmann equation

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