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research and Practice of Cooperative Teaching System for software engineering Major

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计算机教育 2020年第12期 53-59页

作者： Wanjiang Han Jincui Yang Yi Sun Pengfei Sun Xin Jin School of software engineering Beijing University of Posts and TelecommunicationBeijing100876China School Of software engineering BeijingUniversity of Posts and TelecommunicationBeijing100876China

In order to respond to the new engineering construction of the Ministry of Education,and explore the innovative talent training model of collaborative education and multidisciplinary integration,this paper relies on the software engineering teaching team of the School of software engineering,Beijing University of Posts and Telecommunications,through the implementation of the collaborative education project of the Ministry of Education,and proposes the multi-course collaborative practice teaching system,through the reasonable cross-fusion of the practical links of the 5 software engineering courses in the college,realizes the multi-course collaborative education and reasonable cross-fusion of courses,shares practical project resources,introduces new enterprise technologies,and guides students’innovation and entrepreneurship provide a meaningful reference for the collaborative arrangement of teaching content and cross-disciplinary integration in the current university education system.

关键词： collaborative teaching multidisciplinary practical teaching system cross fusion

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A Survey of Link Failure Detection and Recovery in software-Defined Networks

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Computers, Materials & Continua 2025年第1期82卷 103-137页

作者： Suheib Alhiyari Siti Hafizah AB Hamid Nur Nasuha Daud Department of software engineering Universiti MalayaKuala Lumpur50603Malaysia

software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network *** is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional ***,because SDN is designed to ensure high-level service availability,it faces additional *** of themost critical challenges is ensuring efficient detection and recovery from link failures in the data *** failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of *** the recovery process is intrinsically dependent on timely failure detection,this research surveys and analyzes the current literature on both failure detection and recovery approaches in *** survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and ***,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and ***,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.

关键词： software defined networking failure detection failure recovery restoration protection

research on the Construction of Application- Oriented software engineering Semester Training System

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计算机教育 2020年第12期 176-181页

作者： Xiang Wei Jian Zhang Weiwei Xing School of software engineering Beijing Jiaotong UniversityHaidianBeijing100044China

"Semester Training"has been adopted as an important part of the personnel training in software engineering majors since it was first put *** ultimate goal of semester training is to improve the professional quality of students in an all-round way,then eventually achieve the goal of satisfactory employment for both students and ***,in order to achieve the above purpose,the design of traditional training project still has the following problems:the topic selection of traditional training is designed by teachers in college,which lacks the training of engineering ability aiming at practical problems;the content and technology of traditional project training are out of date,ignoring the urgent demand of software industry development for advanced technology application;the traditional project training inspects the mastery of knowledge in each semester Degree,ignores the incremental of a progressive training *** view of the above problems,this study proposes an Application-Oriented software engineering Semester Training *** has proved that the construction of the training system can effectively improve the quality of teaching,so as to further improve the comprehensive quality of students.

关键词： semester training software engineering application-oriented comprehensive quality

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research and Exploration on the Construction of Double Qualified Teachers in software engineering

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计算机教育 2021年第12期 121-125页

作者： Yili Li Guobin Zhu Man Fang Jimin Shi School of Information and software engineering University of Electronic Science and Technology of ChinaChengdu610054China

In order to solve the problem of insufficient integration of school-enterprise supervisors in the current school-enterprise cooperation model,this article introduces the ideas and results of the construction of a team with double-qualified instructors majored in software ***,the integration of production and education are carried out in three stages,i.e.,enterprise cooperation courses,enterprise internship,and graduation design(internship),by taking the software engineering major of the School of Information and software engineering of the University of Electronic Science and Technology of China as a case study.

关键词： software engineering double qualification type faculty development

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Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 909-931页

作者： Adel Binbusayyis Mohemmed Sha Department of software engineering College of Computer engineering and Sciences in Al-Kharj Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia

Prediction of stability in SG(Smart Grid)is essential in maintaining consistency and reliability of power supply in grid *** the fluctuations in power generation and consumption patterns of smart cities assists in effectively managing continuous power supply in the *** also possesses a better impact on averting overloading and permitting effective energy *** though many traditional techniques have predicted the consumption rate for preserving stability,enhancement is required in prediction measures with minimized *** overcome the complications in existing studies,this paper intends to predict stability from the smart grid stability prediction dataset using machine learning *** accomplish this,pre-processing is performed initially to handle missing values since it develops biased models when missing values are mishandled and performs feature scaling to normalize independent data ***,the pre-processed data are taken for training and *** that,the regression process is performed using Modified PSO(Particle Swarm Optimization)optimized XGBoost Technique with dynamic inertia weight update,which analyses variables like gamma(G),reaction time(tau1–tau4),and power balance(p1–p4)for providing effective future stability in *** PSO attains optimal solution by adjusting position through dynamic inertial weights,it is integrated with XGBoost due to its scalability and faster computational speed *** hyperparameters of XGBoost are fine-tuned in the training process for achieving promising outcomes on *** results are measured through evaluation metrics such as MSE(Mean Square Error)of 0.011312781,MAE(Mean Absolute Error)of 0.008596322,and RMSE(Root Mean Square Error)of 0.010636156 and MAPE(Mean Absolute Percentage Error)value of 0.0052 which determine the efficacy of the system.

关键词： Smart Grid machine learning particle swarm optimization XGBoost dynamic inertia weight update

Record-breaking bifunctional oxygen electrocatalyst accomplished by a data-driven approach for zinc-air batteries

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Journal of Energy Chemistry 2025年第1期100卷 144-145页

作者： Deviprasath Chinnadurai Zhi Wei Seh Institute of Materials research and engineering (IMRE) Agency for Science Technology and Research (A*STAR)

Rechargeable zinc-air batteries(ZABs) have recently drawn great attention in energy research due to their high theoretical capacity,low costs, and inherently safe nature [1–3]. However, the sluggish cathode reactions necessitate the development of bifunctional oxygen electrocatalysts with lower ΔE indicator values. The ΔE indicator is commonly employed to quantitatively evaluate the electrocatalytic activity of a bifunctional oxygen electrocatalyst,representing the overall overpotential from oxygen reduction reaction(ORR) to oxygen evolution reaction(OER).

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Traffic safety helmet wear detection based on improved YOLOv5 network

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Optoelectronics Letters 2025年第1期21卷 35-42页

作者： GUI Dongdong SUN Bo College of software Southeast University Quanzhou Equipment research Centre Haixi Institute Chinese Academy of Sciences

Aiming at the problem that the current traffic safety helmet detection model can't balance the accuracy of detection with the size of the model and the poor generalization of the model, a method based on improving you only look once version 5(YOLOv5) is proposed. By incorporating the lightweight Ghost Net module into the YOLOv5 backbone network, we effectively reduce the model size. The addition of the receptive fields block(RFB) module enhances feature extraction and improves the feature acquisition capability of the lightweight model. Subsequently, the high-performance lightweight convolution, GSConv, is integrated into the neck structure for further model size compression. Moreover, the baseline model's loss function is substituted with efficient insertion over union(EIoU), accelerating network convergence and enhancing detection precision. Experimental results corroborate the effectiveness of this improved algorithm in real-world traffic scenarios.

关键词： Traffic control

Deep learning-based software engineering: progress,challenges, and opportunities

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Science China(Information Sciences) 2025年第1期68卷 57-144页

作者： Xiangping CHEN Xing HU Yuan HUANG He JIANG Weixing JI Yanjie JIANG Yanyan JIANG Bo LIU Hui LIU Xiaochen LI Xiaoli LIAN Guozhu MENG Xin PENG Hailong SUN Lin SHI Bo WANG Chong WANG Jiayi WANG Tiantian WANG Jifeng XUAN Xin XIA Yibiao YANG Yixin YANG Li ZHANG Yuming ZHOU Lu ZHANG School of Journalism and Communication Sun Yat-sen University School of software Technology Zhejiang University School of software engineering Sun Yat-sen University School of software Dalian University of Technology School of Computer Science and Technology Beijing Institute of Technology Key Laboratory of High Confidence software Technologies (Peking University) Ministry of EducationSchool of Computer Science Peking University State Key Laboratory for Novel software Technology Nanjing University School of Computer Science and engineering Beihang University Institute of Information engineering Chinese Academy of Sciences School of Computer Science Fudan University State Key Laboratory of Complex & Critical software Environment (CCSE) School of Software Beihang University School of Computer and Information Technology Beijing Jiaotong University School of Computer Science and Technology Harbin Institute of Technology School of Computer Science Wuhan University Huawei Technologies

researchers have recently achieved significant advances in deep learning techniques, which in turn has substantially advanced other research disciplines, such as natural language processing, image processing, speech recognition, and software engineering. Various deep learning techniques have been successfully employed to facilitate software engineering tasks, including code generation, software refactoring, and fault localization. Many studies have also been presented in top conferences and journals, demonstrating the applications of deep learning techniques in resolving various software engineering tasks. However,although several surveys have provided overall pictures of the application of deep learning techniques in software engineering,they focus more on learning techniques, that is, what kind of deep learning techniques are employed and how deep models are trained or fine-tuned for software engineering tasks. We still lack surveys explaining the advances of subareas in software engineering driven by deep learning techniques, as well as challenges and opportunities in each subarea. To this end, in this study, we present the first task-oriented survey on deep learning-based software engineering. It covers twelve major software engineering subareas significantly impacted by deep learning techniques. Such subareas spread out through the whole lifecycle of software development and maintenance, including requirements engineering, software development, testing, maintenance, and developer collaboration. As we believe that deep learning may provide an opportunity to revolutionize the whole discipline of software engineering, providing one survey covering as many subareas as possible in software engineering can help future research push forward the frontier of deep learning-based software engineering more systematically. For each of the selected subareas,we highlight the major advances achieved by applying deep learning techniques with pointers to the available datasets i

关键词： deep learning software engineering software benchmark software artifact representation survey

A Generative Model-Based Network Framework for Ecological Data Reconstruction

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Computers, Materials & Continua 2025年第1期82卷 929-948页

作者： Shuqiao Liu Zhao Zhang Hongyan Zhou Xuebo Chen School of Electronic and Information engineering University of Science and Technology LiaoningAnshan114051China School of Computer Science and software engineering University of Science and Technology LiaoningAnshan114051China

This study examines the effectiveness of artificial intelligence techniques in generating high-quality environmental data for species introductory site selection *** Strengths,Weaknesses,Opportunities,Threats(SWOT)analysis data with Variation Autoencoder(VAE)and Generative AdversarialNetwork(GAN)the network framework model(SAE-GAN),is proposed for environmental data *** model combines two popular generative models,GAN and VAE,to generate features conditional on categorical data embedding after SWOT *** model is capable of generating features that resemble real feature distributions and adding sample factors to more accurately track individual sample *** data is used to retain more semantic information to generate *** model was applied to species in Southern California,USA,citing SWOT analysis data to train the *** show that the model is capable of integrating data from more comprehensive analyses than traditional methods and generating high-quality reconstructed data from them,effectively solving the problem of insufficient data collection in development *** model is further validated by the Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)classification assessment commonly used in the environmental data *** study provides a reliable and rich source of training data for species introduction site selection systems and makes a significant contribution to ecological and sustainable development.

关键词： Convolutional Neural Network(CNN) VAE GAN TOPSIS data reconstruction