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GTE: learning code AST representation efficiently and effectively

Science China(Information Sciences) 2025年第3期68卷 393-394页

作者： Yihao QIN Shangwen WANG Bo LIN Kang YANG Xiaoguang MAO College of Computer Science and Technology National University of Defense Technology Key Laboratory of Software Engineering for Complex Systems National University of Defense Technology

With the development of deep learning in recent years, code representation learning techniques have become the foundation of many software engineering tasks such as program classification [1] and defect detection. Earlier approaches treat the code as token sequences and use CNN, RNN, and the Transformer models to learn code representations.

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Comparing Puncture-Detection Approaches for Manual Needle Insertions Through the Parietal Pleura

IEEE Transactions on Medical Robotics and Bionics

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IEEE Transactions on Medical Robotics and Bionics 2025年第2期7卷 455-468页

作者： L'Orsa, Rachael Zareinia, Kourosh Sutherland, Garnette R. Westwick, David Kuchenbecker, Katherine J. University of Calgary Schulich School of Engineering’s Department of Electrical and Software Engineering Project neuroArm’s Surgical Performance Laboratory Calgary Canada Max Planck Institute for Intelligent Systems Haptic Intelligence Department Stuttgart Germany Toronto Metropolitan University Department of Mechanical Industrial and Mechatronics Engineering Toronto Canada University of Calgary Project neuroArm Cumming School of Medicine Calgary Canada University of Calgary Schulich School of Engineering’s Department of Electrical and Software Engineering Calgary Canada

Tube thoracostomy (chest tube insertion) is a surgical procedure that treats pneumothorax, a potentially life threatening condition where air accumulates between the chest wall and the lungs. The literature reports high complication rates for this procedure, including accidental fatality due to poor manual depth control during tool insertion. We hypothesize that an instrumented needle-holder could help operators recognize pleural puncture and improve depth control, and we present a puncture-detection experiment that contributes toward this goal. An operator manually inserted a bevel-tip needle into ex vivo porcine ribs and through the parietal pleura via a sensorized percutaneous device that records position, force, and videos. We use this rich dataset of 63 insertions to thoroughly test four previously published data-driven puncture-detection (DDPD) algorithms against two new real-time algorithms: a custom recursive digital filter with coefficients optimized for our application, and a difference equation that compares standard deviations between adjacent sliding windows. Our algorithms achieve a precision (true positives over total identified punctures) of 23% and 22%, respectively, while the precision of existing DDPD algorithms ranges from 0% to 21%. Despite these performance improvements, our results show the limitations of DDPD algorithms and motivate new methods for detecting pleural membrane punctures in thoracostomy. © 2018 IEEE.

关键词： Needles

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An Isochron-Based Solution to Pursuit–Evasion Games of Two Heterogeneous Players

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IEEE Transactions on Automatic Control 2025年第5期70卷 2811-2826页

作者： Li, Shuai Wang, Chen Xie, Guangming Peking University State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Beijing100871 China Peking University National Engineering Research Center of Software Engineering Beijing100871 China Peking University Center for Multi-Agent Research Institute for Artificial Intelligence Beijing100871 China

In this article, we study a pursuit–evasion game between two players with heterogeneous kinematics, where the pursuer is with damped double-integrator dynamics and the evader is with single-integrator dynamics. The pursuer aims at capturing the evader as soon as possible, while the evader wants to avoid or delay the capture. Traditional methods to solve pursuit–evasion games rely on the Hamilton–Jacobi–Isaacs (HJI) equations and retrogressive path equations, which are very complicated and nonintuitive, thus failing to obtain a complete solution. To overcome these challenges, we develop an intuitive isochron-based method to thoroughly analyze all possible situations of the game and a concise geometric approach to calculate the optimal strategies, providing a complete solution to this game. Specifically, the isochron-based method effectively leverages three main factors: the players' motion capability, the pursuer's capture capability, and the players' states. Based on these, we analyze the players' superiority and the geometrical features of their isochrones and the intersections, thus acquiring concise conditions that determine the game's outcome. For the success-capture cases, we propose a new geometric approach to calculate the target points of the players and then obtain the closed-loop state feedback optimal pursuit and evasion strategies. We then get the corresponding value function and provide a validation using the HJI equation. For the success-evasion cases, we exploit the intersection of the players' isochrones to design some effective evasion strategies, which ensure that the evader can always avoid or delay the capture. Finally, some numerical simulations are carried out to validate the effectiveness and applicability of our results. © 1963-2012 IEEE.

关键词： State feedback

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Distributed Task Allocation With Minimum Makespan for Heterogeneous Multiplayer Pursuit–Evasion Games

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IEEE Transactions on Automatic Control 2025年第5期70卷 2827-2842页

作者： Li, Shuai Wang, Chen Sun, Jinan Zhang, Shikun Xie, Guangming Peking University State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Beijing100871 China Peking University National Engineering Research Center of Software Engineering Beijing100871 China Peking University Center for Multi-Agent Research Institute for Artificial Intelligence Beijing100871 China

In the domain of multiplayer pursuit–evasion games, it is crucial to address the practical aspects of the players' heterogeneity, the distributed control manner, and the pursuers' goal of minimum makespan. However, the three topics have received limited attention in existing literature, both separately and in combination. In this article, we address the multiplayer pursuit–evasion game integrating these key topics, where the pursuers with simple motions strive to capture as many evaders, characterized by damped double integrators, as possible, meanwhile minimizing the task makespan. To this end, we establish an overall framework and sequentially tackle four key issues, leading to an effective solution to the entire problem. We first propose a novel isochron-based method to derive the capture condition and acquire the optimal pursuit and evasion strategies. Then, we enhance the usability of the capture condition by geometrically deriving the analytical form of the pursuer's winning region with respect to a given evader. Third, leveraging the concept of winning regions, we determine the lower boundary of pursuers' sensing range, ensuring sufficient information acquisition for evader allocation while avoiding selection conflicts. Finally, we propose a fully distributed allocation algorithm for each pursuer allowing the pursuer team to converge to the optimal evader allocation. By combining these contributions, we successfully provide an effective solution to the entire problem. Various simulations are conducted to show the effectiveness of our proposed methods. © 1963-2012 IEEE.

关键词： Games Resource management Sensors Robot sensing systems Mathematical models Heuristic algorithms Decentralized control Usability Biomimetics Topology

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Advances in Robust Federated Learning: A Survey with Heterogeneity Considerations

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IEEE Transactions on Big Data 2025年第03期11卷 1548-1567页

作者： Chen, Chuan Liao, Tianchi Deng, Xiaojun Wu, Zihou Huang, Sheng Zheng, Zibin Sun Yat-sen University School of Computer Science and Engineering Guangzhou510006 China Guangdong Key Laboratory of Big Data Analysis and Processing China Sun Yat-sen University School of Software Engineering Zhuhai519000 China Sun Yat-sen University School of Systems Science and Engineering Guangzhou510006 China Zhuhai Key Laboratory of Trusted Large Language Models China

In the field of heterogeneous federated learning (FL), the key challenge is to efficiently and collaboratively train models across multiple clients with different data distributions, model structures, task objectives, computational capabilities, and communication resources. This diversity leads to significant heterogeneity, which increases the complexity of model training. In this paper, we first outline the basic concepts of heterogeneous FL and summarize the research challenges in FL in terms of five aspects: data, model, task, device and communication. In addition, we explore how existing state-of-the-art approaches cope with the heterogeneity of FL, and categorize and review these approaches at three different levels: data-level, model-level, and architecture-level. Subsequently, the paper extensively discusses privacy-preserving strategies in heterogeneous FL environments. Finally, the paper discusses current open issues and directions for future research, aiming to promote the further development of heterogeneous FL. © 2015 IEEE.

关键词： Federated learning

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Understanding and Identifying Technical Debt in the Co-Evolution of Production and Test Code

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IEEE Transactions on software engineering 2025年第05期51卷 1415-1436页

作者： Guo, Yimeng Chen, Zhifei Xiao, Lu Chen, Lin Li, Yanhui Zhou, Yuming Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China Nanjing University of Science and Technology School of Computer Science and Engineering Nanjing210094 China Stevens Institute of Technology School of Systems and Enterprises HobokenNJ07030 United States

The co-evolution of production and test code (PT co-evolution) has received increasing attention in recent years. However, we found that existing work did not comprehensively study various PT co-evolution scenarios, such as the qualification and persistence of their effects on software. Inspired by technical debt (TD), we refer to TD generated during the co-evolution between production and test code as PT co-evolution technical debt (PTCoTD). To better understand PT co-evolution, we first conducted an exploratory study on its characteristics on 15 open-source projects, finding unbalanced PT co-evolution prevalent and summarizing five potential PT flaws. Then we proposed an approach to identify and quantify PTCoTDs of these flaw patterns, considering evolutionary and structural relationships. We also built prediction models to describe cost trajectories and rank all PTCoTDs to prioritize expensive ones. The evaluation on the 15 projects shows that our approach can identify PTCoTDs that deserve attention. The identified PTCoTDs account for about half of the project's total maintenance costs, and the cost proportion of the expensive Top-5 is 1.8x more than the file proportion they contain. Almost all covered maintenance costs persist as PTCoTD in the future, with an average increase of 6.8% between the last two releases. Our approach also accurately predicts the costs of PTCoTD with an average prediction deviation of only 8.3%. Our study provides valuable insights into PT co-evolution scenarios and their effects, which can guide practices and inspire future work on software testing and maintenance. © 2025 IEEE.

关键词： software testing

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Vision DualGNN: Semantic Graph Is Not Only You Need 27th

Vision DualGNN: Semantic Graph Is Not Only You Need

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Zheng, Xiaolong Wang, Jianming Xiao, Zhitao Sun, Yukuan School of Software Tiangong University Tianjin China Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tiangong University Tianjin China Tianjin Key Laboratory of Optoelectronic Detection Technology and Systems Tiangong University Tianjin China Center for Engineering Intership and Training Tiangong University Tianjin China

ISBN: (纸本)9783031781063

Graph Neural Networks (GNNs) have shown great potential in visual tasks, yet they face challenges in effectively constructing and processing graphs. Vision GNN (ViG) was developed to tackle these issues by segmenting images into patches treated as nodes, with edges formed by connecting the nearest semantic neighbors. However, relying solely on semantic information for graph construction confines itself to a dispersed distribution of object neighbors, leading to inadequate graph processing. To address this issue, we propose Vision DualGNN(VDG), a novel dual graph neural network architecture that leverages both spatial and semantic information to construct and process graph representation of images. We apply a node encoder that transforms image patches into expressive node features. Additionally, we implement a dual-stream GNN that operates on both a spatial graph and a semantic graph. The spatial graph serves as a constraint for the semantic graph, enhancing the node features with spatial awareness. To verify the validity of our architecture, we have conducted our experiments on the ImageNet and CIFAR-100 datasets. And achieved state-of-the-art performance compared to other baseline models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： dualgnn graph convolution semantic graph spatial graph

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Against Mobile Collusive Eavesdroppers: Cooperative Secure Transmission and Computation in UAV-Assisted MEC Networks

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IEEE Transactions on Mobile Computing 2025年第6期24卷 5280-5297页

作者： Zhao, Mingxiong Wang, Zirui Guo, Kun Zhang, Rongqian Quek, Tony Q. S. Ministry of Education Engineering Research Center of Integration and Application of Digital Learning Technology Beijing100039 China Ministry of Education Engineering Research Center of Cyberspace Kunming650504 China Yunnan University of Finance and Economics Yunnan Key Laboratory of Service Computing Kunming650221 China Yunnan University Yunnan Key Laboratory of Software Engineering Kunming650091 China East China Normal University Shanghai Key Laboratory of Multidimensional Information Processing School of Communications and Electronics Engineering Shanghai200241 China Yunnan University School of Information Science and Engineering Kunming650500 China Singapore University of Technology and Design Information Systems Technology and Design 487372 Singapore National Pilot School of Software Yunnan University Kunming China

In Unmanned Aerial Vehicle (UAV)-assisted Mobile Edge Computing (MEC) networks, the security of transmission faces significant challenges due to the vulnerabilities of line-of-sight links and potential eavesdropping on two-hop links. This paper addresses these challenges with an innovative Cooperative Secure Transmission and Computation strategy (CSTC), specifically engineered for time-slotted UAV-assisted MEC networks plagued by mobile collusive eavesdroppers. These eavesdroppers significantly bolster their interception capabilities through coordinated and optimized movements, escalating the security threats. To neutralize these risks, the proposed CSTC employs the UAV and remote devices as helper nodes to emit jamming signals, thereby thwarting eavesdropping activities, while simultaneously facilitating the efficient relay of users' tasks to the base station for advanced processing. The CSTC aims to maximize the sum Secrecy Transmission Rate (STR) satisfying task latency constraints. It involves a joint optimization of UAV trajectory, jamming beamformers, transmit power, and data offloading strategy to expedite task transmission. Additionally, a real-time computation scheduling approach is developed based on a newly defined metric, the Urgency Degree of Users (UDoU), to enhance task processing efficiency. Our extensive simulations validate that the CSTC not only elevates the sum STR but also consistently meets latency constraints, demonstrating its robustness against advanced mobile eavesdropping techniques. © 2002-2012 IEEE.

关键词： Jamming

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D-VSync: Decoupled Rendering and Displaying for Smartphone Graphics 25

D-VSync: Decoupled Rendering and Displaying for Smartphone G...

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30th ACM International Conference on Architectural Support for Programming Languages and Operating systems, ASPLOS 2025

作者： Wu, Yuanpei Du, Dong Xu, Chao Xia, Yubin Fu, Ming Zang, Binyu Chen, Haibo Ipads Shanghai Jiao Tong University Engineering Research Center for Domain-specific Operating Systems Ministry of Education Shanghai China Fields Lab Huawei Central Software Institute Shanghai China Fields Lab Huawei Central Software Institute Hangzhou China Ipads Shanghai Jiao Tong University Engineering Research Center for Domain-specific Operating Systems Ministry of Education Key Laboratory of System Software Chinese Academy of Science Shanghai China

ISBN: (纸本)9798400706981

Rendering service, which typically orchestrates screen display and UI through Vertical Synchronization (VSync), is an indispensable system service for user experiences of smartphone OSes (e.g., Android, OpenHarmony, and iOS). The recent trend of large high-frame-rate screens, stunning visual effects, and physics-based animations has placed unprecedented pressure on the VSync-based rendering architecture, leading to higher frame drops and longer rendering latency. This paper proposes Decoupled Vertical Synchronization (D-VSync), which decouples execution and displaying in the rendering service. D-VSync allows frames to be rendered a number of VSync periods before being physically displayed on the screen. The key insight behind D-VSync to resolve the limitation of VSync is that, the decoupling enables sporadic long frames to utilize the computational power saved by common short frames, therefore providing a larger time window to tolerate workload fluctuations. Evaluation results of 75 common OS use cases and apps on OpenHarmony (Mate 40 Pro, Mate 60 Pro), 25 popular apps on Android (Google Pixel 5), and simulations of 15 mobile games show that compared to VSync, D-VSync on average reduces frame drops by 72.7%, user-perceptible stutters by 72.3%, and rendering latency by 31.1%, with only 0.13%-0.37% more power consumption. D-VSync has been integrated into HarmonyOS NEXT. © 2025 ACM.

关键词： Rendering (computer graphics)

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YFLM: An Improved Levenberg-Marquardt Algorithm for Global Bundle Adjustment 41st

YFLM: An Improved Levenberg-Marquardt Algorithm for Global ...

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41st Computer Graphics International Conference, CGI 2024

作者： Peng, Jiaxin Li, Tao Jiang, Qin Liu, Jie Wang, Ruibo Laboratory of Software Engineering for Complex Systems School of Computer Science National University of Defense Technology Hunan Changsha410073 China Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Hunan Changsha410073 China

ISBN: (纸本)9783031820205

The conventional Levenberg-Marquardt (LM) algorithm is a state-of-the-art trust-region optimization method for solving bundle adjustment problems in the Structure-from-Motion community, which not only takes advantage of the fast convergence of the Gauss-Newton method, but also the stability of the gradient descent method when approaching optimal solutions. However, the damping ratio of LM is simply provided by trial-and-error, which causes slow convergence rate for large-scale problems. This paper proposes the Yamashita-Fukushima LM (YFLM) algorithm to reduce the time complexity for global bundle adjustment, where the damping factor is determined by Yamashita and Fukushima’s method. YFLM dynamically calculates a more reasonable and optimal damping ratio according to the newest reprojection error. The experimental results show that the YFLM algorithm outperforms the conventional LM algorithm for most public bundle adjustment datasets. Besides this, the convergence of the YFLM algorithm is also evaluated with different σ∈(0,2]. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Damping

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