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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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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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Transformer-Based Scenario Generation of Multi-segment Monotonic Increasing Bidding Curves of Power Plants

Transformer-Based Scenario Generation of Multi-segment Monot...

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International Conference of Electrical, Electronic and Networked Energy systems, EENES 2024

作者： Xie, Haochuan Lv, Jianhu Wang, Ying Yuan, Kun College of Software Southeast University Suzhou China China Electric Power Research Institute Beijing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (纸本)9789819618637

With the relaxation of electricity market regulation, power plants are permitted to engage in bidding. The bidding outcomes in the competitive market differ significantly from those in the previously regulated market. These differences in bidding outcomes will further impact power flow and system security. To provide a reference for practical electricity market operations, make market simulation more realistic, it is crucial to analyze and establish a model to simulate the bidding behavior of power generators. This paper applies Transformer networks to predict multi-segment bidding behaviors of power plants, we have improved the classic Transformer network by adopting a one encoder-two decoder format, considering six key factors influencing bidding behavior: unit ID, fuel type, capacity, location, system load, and load ratio. Additionally, monotonicity of the multi-segment bidding curves of power plants is taken into account, and monotonicity loss functions are introduced to achieve this goal. We apply this method to predict bidding behaviors in power plants in the Australian electricity market, validating the accuracy of the model. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： bidding curves generation monotonicity constraint power market Transformer-based

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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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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (Science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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Distributed MPC Compensation-Based LFC for Heterogeneous Multi-area Interconnected Power systems 8th

Distributed MPC Compensation-Based LFC for Heterogeneous Mul...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Chi, Xiaobo Li, Xinyi Liu, Xiaolin Jia, Xinchun School of Automation and Software Engineering Shanxi University Taiyuan030031 China School of Mathematical Sciences Shanxi University Taiyuan030006 China The Key Laboratory of Complex Systems and Data Science Ministry of Education Taiyuan030006 China

ISBN: (纸本)9789819602247

This paper addresses the distributed load frequency control (LFC) problem for multi-area interconnected power systems (MAIPSs) with thermal and wind power generations, considering both inter-area and intra-area transmission delays and random packet losses induced by communication networks. Firstly, a heterogeneous framework of MAIPSs is constructed, where a networked distributed model predictive control (DMPC) scheme is proposed to compensate for transmission delays and random packet losses. Based on this framework, we then developed a distributed closed-loop LFC system model for heterogeneous MAIPS. Subsequently, a Luenberger observer is constructed to estimate the system state of the local area, and a networked feedback controller is designed to ensure stability with a certain H∞ performance level for the networked MAIPSs. Moreover, stability conditions and controller design criteria are provided by using the Lyapunov-Krasovskii stability theory. Finally, the control performance of the proposed method is verified through an example of a two-area interconnected power system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Predictive control systems

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Exploring Communication-efficient Federated Learning via Stateless In-network Aggregation

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IEEE Transactions on Mobile Computing 2025年

作者： Xia, Junxu Cheng, Geyao Wu, Wenfei Luo, Lailong Guo, Deke National University of Defense Technology National Key Laboratory of Information Systems Engineering Changsha Hunan410073 China National University of Defense Technology State Key Laboratory of Complex & Critical Software Environment College of Information and Communication Changsha Hunan410073 China Peking University School of Computer Science Beijing100091 China

As an ambitious training paradigm, federated learning has garnered increasing attention in recent years, which enables collaborative training of a global model without accessing users' private data. However, due to the simultaneous and constant model updates gathering from massive distributed clients, the central server generally becomes a performance bottleneck. Additionally, the stateful aggregation (retaining all the updates from each client) conducted by the central server further poses potential threats to privacy, since it may recover the raw data based on such model updates inversely. The state-of-the-art methodologies, however, fail to address these two problems concurrently and efficiently. To this end, we propose GAIN, a secure aggregation acceleration service for federated learning. At its core, GAIN leverages programmable switches deployed at the edge network to aggregate model updates in a stateless manner before transmitting them to the central server. Consequently, GAIN can accelerate the transmission and aggregation of model updates while eliminating the chance of recovering private data. We evaluate the performance of GAIN through FPGA-based experiments and large-scale simulations. The results show that GAIN can effectively reduce bandwidth overhead and achieve up to 4.11× training throughput acceleration while prioritizing privacy protection. © 2025 IEEE.

关键词： Differential privacy

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Towards Connecting Discrete Mathematics and software engineering

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Tsinghua Science and Technology 2020年第3期25卷 325-335页

作者： Tun Li Wanwei Liu Juan Chen Xiaoguang Mao Xinjun Mao the School of Computer National University of Defense Technology and are also with Laboratory of Software Engineering for Complex Systems

To enhance training in software development,we argue that students of software engineering should be exposed to software development activities early in the *** entails meeting the challenge of engaging students in software development before they take the software engineering *** this paper,we propose a method to connect courses in the software engineering curriculum by setting comprehensive development projects to students in prerequisite courses for software *** the Discrete Mathematics(DM)course as an example,we describe the implementation of the proposed method and teaching practices using several practical and comprehensive projects derived from topics in discrete *** descriptions of the sample projects,their application,and training results are *** and lessons learned from applying these practices show that it is a promising way to connect courses in the software engineering curriculum.

关键词： Discrete Mathematics(DM) software engineering proof checker database management system symbolic execution engine

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ForkXplorer:an approach of fork summary generation

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Frontiers of Computer Science 2022年第2期16卷 1-15页

作者： Zhang ZHANG Xinjun MAO Chao ZHANG Yao LU Key Laboratory of Software Engineering for Complex Systems College of ComputerNational University of Defense TechnologyChangsha 410073China

Pull-based development has become an important paradigm for distributed software *** this model,each developer independently works on a copied repository(i.e.,a fork)from the central *** is essential for developers to maintain awareness of the state of other forks to improve collaboration *** this paper,we propose a method to automatically generate a summary of a *** first use the random forest method to generate the label of a fork,i.e.,feature implementation or a bug *** on the information of the fork-related commits,we then use the TextRank algorithm to generate detailed activity information of the ***,we apply a set of rules to integrate all related information to construct a complete fork *** validate the effectiveness of our method,we conduct 30 groups of manual experiment and 77 groups of case studies on *** propose Fea_(avg)to evaluate the performance of Fea_(avg)the generated fork summary,considering the content accuracy,content integrity,sentence fluency,and label extraction *** results show that the average of of the fork summary generated by this method is *** than 63%of project maintainers and the contributors believe that the fork summary can improve development efficiency.

关键词： open source software pull-based development fork summary distributed cooperative development

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