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Bug localization based on syntactical and semantic information of source code

Journal of Systems Engineering and Electronics 2023年第1期34卷 236-246页

作者： YAN Xuefeng CHENG Shasha GUO Liqin College of Computer Science Technology Nanjing University of Aeronautics and AstronauticsNanjing 211106China Collaborative Innovation Center of Novel Software Technology and Industrialization Nanjing 211106China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System EngineeringBeijing 100854China

The existing software bug localization models treat the source file as natural language, which leads to the loss of syntactical and structure information of the source file. A bug localization model based on syntactical and semantic information of source code is proposed. Firstly, abstract syntax tree(AST) is divided based on node category to obtain statement sequence. The statement tree is encoded into vectors to capture lexical and syntactical knowledge at the statement ***, the source code is transformed into vector representation by the sequence naturalness of the statement. Therefore,the problem of gradient vanishing and explosion caused by a large AST size is obviated when using AST to the represent source code. Finally, the correlation between bug reports and source files are comprehensively analyzed from three aspects of syntax, semantics and text to locate the buggy code. Experiments show that compared with other standard models, the proposed model improves the performance of bug localization, and it has good advantages in mean reciprocal rank(MRR), mean average precision(MAP) and Top N Rank.

关键词： bug report abstract syntax tree code representation software bug localization

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Discriminative Word Alignment Over Multiple Word Segmentations

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Chinese Journal of Electronics 2025年第2期23卷 263-270页

作者： Ning Xi Xinyu Dai Shujian Huang Jiajun Chen Department of Computer Science and Technology State Key Laboratory for Novel Software Technology Nanjing University Nanjing China

Conventional bilingual word alignment is conducted on sentence pairs with single word segmentation for languages such as Chinese, viz. Single-segmentation-based word alignment (SSWA). However, SSWA may run the risk of losing optimal word segmentation granularities or causing data sparseness in word alignment. This paper proposes Multiple-segmentation-based word alignment (MSWA). In MSWA, diverse and complementary knowledge in multiple word segmentations can be employed to lower the above risks in word alignment. Given $k$ word segmentations of a Chinese sentence, a skeleton segmentation is firstly constructed. The alignment between the skele-ton segmentation and the parallel English sentence is log-linearly modeled, where various features defined over multiple word segmentations are incorporated. The Viterbi alignment, the alignment with the highest score, is mapped back to $k$ word alignments based on $k$ segmentations respectively. Experimentally, MSWA outperformed SSWA on all $k$ segmentations in both alignment quality and translation performance.

关键词： Translation Viterbi algorithm Social sciences Education Medical services Skeleton

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The Computational Advantage of MIP∗ Vanishes in the Presence of Noise 39

The Computational Advantage of MIP∗ Vanishes in the Presenc...

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39th Computational Complexity Conference, CCC 2024

作者： Dong, Yangjing Fu, Honghao Natarajan, Anand Qin, Minglong Xu, Haochen Yao, Penghui State Key Laboratory for Novel Software Technology Nanjing University China Massachusetts Institute of Technology CambridgeMA United States State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Hefei National Laboratory China

ISBN: (纸本)9783959773317

The class MIP∗ of quantum multiprover interactive proof systems with entanglement is much more powerful than its classical counterpart MIP [7, 29, 28]: while MIP = NEXP, the quantum class MIP∗ is equal to RE, a class including the halting problem. This is because the provers in MIP∗ can share unbounded quantum entanglement. However, recent works [46, 47] have shown that this advantage is significantly reduced if the provers’ shared state contains noise. This paper attempts to exactly characterize the effect of noise on the computational power of quantum multiprover interactive proof systems. We investigate the quantum two-prover one-round interactive system MIP∗ [poly, O(1)], where the verifier sends polynomially many bits to the provers and the provers send back constantly many bits. We show noise completely destroys the computational advantage given by shared entanglement in this model. Specifically, we show that if the provers are allowed to share arbitrarily many EPR states, where each EPR state is affected by an arbitrarily small constant amount of noise, the resulting complexity class is equivalent to NEXP = MIP. This improves significantly on the previous best-known bound of NEEEXP (nondeterministic triply exponential time) [46]. We also show that this collapse in power is due to the noise, rather than the O(1) answer size, by showing that allowing for noiseless EPR states gives the class the full power of RE = MIP∗ [poly, poly]. Along the way, we develop two technical tools of independent interest. First, we give a new, deterministic tester for the positivity of an exponentially large matrix, provided it has a low-degree Fourier decomposition in terms of Pauli matrices. Secondly, we develop a new invariance principle for smooth matrix functions having bounded third-order Fréchet derivatives or which are Lipschitz continuous. © Yangjing Dong, Honghao Fu, Anand Natarajan, Minglong Qin, Haochen Xu, and Penghui Yao.

关键词： Fourier analysis

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Quantum Pseudorandom Scramblers 22nd

Quantum Pseudorandom Scramblers

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22nd Theory of Cryptography Conference, TCC 2024

作者： Lu, Chuhan Qin, Minglong Song, Fang Yao, Penghui Zhao, Mingnan Computer Science Department Portland State University Portland United States State Key Laboratory for Novel Software Technology Nanjing University Nanjing210023 China Hefei National Laboratory Hefei230088 China

ISBN: (纸本)9783031780165

Quantum pseudorandom state generators (PRSGs) have stimulated exciting developments in recent years. A PRSG, on a fixed initial (e.g., all-zero) state, produces an output state that is computationally indistinguishable from a Haar random state. However, pseudorandomness of the output state is not guaranteed on other initial states. In fact, known PRSG constructions provably fail on some initial states. In this work, we propose and construct quantum Pseudorandom state Scramblers (PRSSs), which can produce a pseudorandom state on an arbitrary initial state. In the information-theoretical setting, we obtain a scrambler which maps an arbitrary initial state to a distribution of quantum states that is close to Haar random in total variation distance. As a result, our scrambler exhibits a dispersing property. Loosely, it can span an ϵ-net of the state space. This significantly strengthens what standard PRSGs can induce, as they may only concentrate on a small region of the state space provided that the average output state approximates a Haar random state. Our PRSS construction develops a parallel extension of the famous Kac’s walk, and we show that it mixes exponentially faster than the standard Kac’s walk. This constitutes the core of our proof. We also describe a few applications of PRSSs. While our PRSS construction assumes a post-quantum one-way function, PRSSs are potentially a weaker primitive and can be separated from one-way functions in a relativized world similar to standard PRSGs. © International Association for Cryptologic Research 2025.

关键词： Distribution functions

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On the Fine-Grained Query Complexity of Symmetric Functions 34

On the Fine-Grained Query Complexity of Symmetric Functions

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34th International Symposium on Algorithms and Computation, ISAAC 2023

作者： Podder, Supartha Yao, Penghui Ye, Zekun Department of Computer Science Stony Brook University New YorkNY United States State Key Laboratory for Novel Software Technology Nanjing University China Hefei National Laboratory China State Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9783959772891

Watrous conjectured that the randomized and quantum query complexities of symmetric functions are polynomially equivalent, which was resolved by Ambainis and Aaronson [1], and was later improved in [15, 12]. This paper explores a fine-grained version of the Watrous conjecture, including the randomized and quantum algorithms with success probabilities arbitrarily close to 1/2. Our contributions include the following: 1. An analysis of the optimal success probability of quantum and randomized query algorithms of two fundamental partial symmetric Boolean functions given a fixed number of queries. We prove that for any quantum algorithm computing these two functions using T queries, there exist randomized algorithms using poly(T) queries that achieve the same success probability as the quantum algorithm, even if the success probability is arbitrarily close to 1/2. These two classes of functions are instrumental in analyzing general symmetric functions. 2. We establish that for any total symmetric Boolean function f, if a quantum algorithm uses T queries to compute f with success probability 1/2 + β, then there exists a randomized algorithm using O(T2) queries to compute f with success probability 1/2 + Ω (δβ2) on a 1 − δ fraction of inputs, where β, δ can be arbitrarily small positive values. As a corollary, we prove a randomized version of Aaronson-Ambainis Conjecture [1] for total symmetric Boolean functions in the regime where the success probability of algorithms can be arbitrarily close to 1/2. 3. We present polynomial equivalences for several fundamental complexity measures of partial symmetric Boolean functions. Specifically, we first prove that for certain partial symmetric Boolean functions, quantum query complexity is at most quadratic in approximate degree for any error arbitrarily close to 1/2. Next, we show exact quantum query complexity is at most quadratic in degree. Additionally, we give the tight bounds of several complexity measures, indicating their p

关键词： Quantum theory

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RSCache: A Tail Latency Friendly Cache Based on NVMe SSDs 22

RSCache: A Tail Latency Friendly Cache Based on NVMe SSDs

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22nd IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024

作者： Lu, Jincheng Cai, Miao Ye, Baoliu Hohai University College of Computer Science and Software Engineering Nanjing China Nanjing University of Aeronautics and Astronautics College of Computer Science and Technology Nanjing China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China

ISBN: (纸本)9798331509712

High fan-out requests are prevalent in systems employing multi-tier architectures. These requests are divided into several sub-requests for parallel processing. However, a high fan-out request must await all sub-requests to be completed before returning, but the processing times of sub-requests are unpredictable due to their differences in characteristics, such as data volume and data popularity. Meanwhile, existing SSD-based caches struggle to adjust request processing speeds to ensure timely handling. As a result, some sub-requests are delayed, affecting the overall latency and causing long tail latency *** paper proposes RSCache, a tail latency-friendly cache based on NVMe SSDs. RSCache combines the NVMe Weighted Round-robin (WRR) arbitration mechanism with a priority-based scheduling mechanism to enable differentiated request processing. We propose a fan-out size-based priority assignment strategy along with a latency-aware sub-request sorting method. They collaborate to prioritize sub-requests according to their impacts on tail latency and schedule them to NVMe priority queues with various processing speeds, effectively reducing the processing time variations among sub-requests. In addition, we balance the load across queues to avoid congestion with a novel feedback mechanism. We implement the prototype of RSCache based on SPDK. Our experiments demonstrate that RSCache reduces tail latency by up to 40% and improves throughput by two times compared to state-of-the-art SSD-based cache designs. © 2024 IEEE.

关键词： Parallel architectures

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Speech Recognition Method Based on Deep Learning of Artificial Intelligence: An example of BLSTM-CTC model 2023

Speech Recognition Method Based on Deep Learning of Artifici...

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5th International Symposium on Signal Processing Systems, SSPS 2023

作者： Chen, Kangyu Peng, Zhiyuan Department of Computer Science The University of Hong Kong Hong Kong State Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9798400700040

Under the influence of information, network and intelligent high-speed development situation, China's intelligent technology and other aspects have made great progress and achievements, derived a lot of advanced artificial intelligence technology, machine learning technology and deep learning technology, etc., to promote the development of intelligence and information in major fields. Artificial intelligence deep learning is the fusion of artificial intelligence technology and machine learning technology, which lays the foundation for the reform and innovation of artificial voice intelligent recognition technology and intelligent robot technology. So in order to improve the application level of intelligent speech recognition technology, it is necessary to continuously optimize the speech recognition method based on AI deep learning. In this regard, according to the relevant literature, this paper addresses the problem that phoneme features of varying duration are generated during the propagation of speech signals, and these features affect the correct rate of speech recognition, and the phoneme features of different lengths are standardized based on the deep learning research mentioned in this paper with BLSTM-CTC as an example. By evaluating the model on the Thchs30 and ST-CMDS datasets, the results show that the MCFN-based BLSTM-CTC speech recognition model has a reduced recognition word error rate compared with the traditional speech recognition model. © 2023 ACM.

关键词： Speech recognition

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Detecting Double Mixed Compressed Images Based on Quaternion Convolutional Neural Network

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Chinese Journal of Electronics 2024年第3期33卷 657-671页

作者： Hao WANG Jinwei WANG Xuelong HU Bingtao HU Qilin YIN Xiangyang LUO Bin MA Jinsheng SUN Department of Automation Nanjing University of Science and Technology Engineering Research Center of Digital Forensics Ministry of Education Department of Computer and Software Nanjing University of Information Science and Technology School of Management Nanjing University of Posts and Telecommunications Department of Computer Science and Engineering Guangdong Province Key Laboratory of Information Security Technology Sun Yat-sen University State Key Laboratory of Mathematical Engineering and Advanced Computing Qilu University of Technology

Detection of color images that have undergone double compression is a critical aspect of digital image *** the existence of various methods capable of detecting double Joint Photographic Experts Group(JPEG) compression,they are unable to address the issue of mixed double compression resulting from the use of different compression *** particular,the implementation of Joint Photographic Experts Group 2000(JPEG2000)as the secondary compression standard can result in a decline or complete loss of performance in existing *** tackle this challenge of JPEG+JPEG2000 compression,a detection method based on quaternion convolutional neural networks(QCNN) is *** QCNN processes the data as a quaternion,transforming the components of a traditional convolutional neural network(CNN) into a quaternion *** relationships between the color channels of the image are preserved,and the utilization of color information is ***,the method includes a feature conversion module that converts the extracted features into quaternion statistical features,thereby amplifying the evidence of double *** results indicate that the proposed QCNN-based method improves,on average,by 27% compared to existing methods in the detection of JPEG+JPEG2000 compression.

关键词： Color image forensics JPEG JPEG2000 Mixed double compression Quaternion convolutional neural network

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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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25th International Conference on Web Information Systems Engineering, WISE 2024

作者： Tu, Longchuan Meng, Shunmei Liu, Xiao Liu, Guanfeng Beheshti, Amin Zhang, Xuyun School of Computer Science and Engineering Nanjing University of Science and Technology Nanjin China State Key Laboratory for Novel Software Technology Nanjing University Nanjin China School of Computing Macquarie University Sydney Australia

ISBN: (纸本)9789819605699

Recently, graph neural networks(GNNs) have played a key crucial in many recommendation situations. In particular, contrastive learning-based hypergraph neural networks (HGNNs) are gradually becoming a research focus for addressing issues of data sparsity and noise. Despite many studies proving their outstanding performance, there are still some shortcomings: i) Most contrastive learning-based HGNNs primarily rely on cross-view contrastive learning, while neglecting contrastive learning on the interaction graph. ii) Utilizing node embedding for hypergraph structure learning is susceptible to the influence of low-quality representations, thereby constraining the learning capability of HGNNs. To address these issues, we offer a Semantic Similarity-based Graph Contrastive Learning framework (SSGCL), which aims to jointly learn representations with rich semantic information through within-view and cross-view contrastive learning. Specifically, we first introduce consistency contrastive learning, which captures self-supervised signals through semantic similarity between nodes and their neighborhoods. It better captures the unique features of nodes through the connections between nodes and their neighborhoods. Then, we utilize interaction graph learning hypergraph structure, promoting it to extract potential node connections and thus improving its ability to describe homogeneous node relationships. Experimental evaluations on three actual datasets show that SSGCL performs much better than the current baseline models. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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