The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seco...The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.展开更多
Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings...Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.展开更多
Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of am...Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of amyloidbeta(Aβ)and ta u accumulation-the molecular hallmarks of AD-structural magnetic resonance imaging(MRI),assessments of brain metabolism,and,more recently,blood-based markers),a definitive diagnosis of AD continues to be challenging.For example,Frisoni et al.展开更多
Oligodendrocytes and their cell-intrinsic gene regulatory network:Oligodendrocytes(OLs)are the myelinating glial cells of the vertebrate central nervous system.They are responsible for insulating neuronal axons with a...Oligodendrocytes and their cell-intrinsic gene regulatory network:Oligodendrocytes(OLs)are the myelinating glial cells of the vertebrate central nervous system.They are responsible for insulating neuronal axons with a lipid-rich myelin sheath,which enables the saltatory conduction of action potentials.During development,oligodendrocyte progenitor cells(OPCs)emerge from neural stem cells in the ventricular zone.They then proliferate,increase their number,and migrate to their final destination where they encounter unmyelinated neuronal axons and differentiate in a stepwise fashion into myelinating oligodendrocytes(mOLs)under the influence of environmental stimuli.展开更多
Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and ...Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and secretary of the CPC Gulu Village Branch,better known as Cliff Village,in Hanyuan County,Ya’an City,Sichuan Province,was still dressed in his Yi ethnic waistcoat.展开更多
Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniq...Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniques coming up rapidly.The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way forward.This review follows Kitchenham’s review protocol.The review has been divided into three main stages including planning,execution,and analysis.From the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation techniques.Quantifying risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation efforts.Through a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat landscape.The review reveals that threat analysis and security testing are needed to develop automated tools for the future.Accurate estimation of effort required to prioritize potential security risks is a big challenge in software security.The accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep learning.It is also imperative to validate these effort estimation methods to ensure all potential security threats are addressed.Another challenge is selecting the right model for each specific security threat.To achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.展开更多
Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accu...Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.展开更多
The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three ...The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.展开更多
Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhance...Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since 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 SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.展开更多
The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engin...The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engineering into IoT engineering education remains underexplored.To address this gap,the School of Software at North University of China,in collaboration with QST Innovation Technology Group Co.,Ltd.(QST),has developed an innovative educational mechanism.This initiative focuses on the software engineering IoT track and optimizes the teaching process through the outcome-based education(OBE)concept.It incorporates military-industrial characteristics,introduces advanced information and technology curricula,and enhances laboratory infrastructure.The goal is to cultivate innovative talents with unique capabilities,thereby fostering the comprehensive development and application of IoT technology.展开更多
Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive s...Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.展开更多
In recent years,automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market.The integration of artificial intelligence(AI)tools,particularly those us...In recent years,automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market.The integration of artificial intelligence(AI)tools,particularly those using natural language processing(NLP)like ChatGPT,has opened new possibilities for automating various stages of the development lifecycle.The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development.An artificial intelligence(AI)tool was developed using the OpenAI—Application Programming Interface(API),incorporating two key functionalities:1)generating user stories based on case or process inputs,and 2)estimating the effort required to execute each user story.Additionally,ChatGPT was employed to generate application code.The AI tool was tested in three case studies,each explored under two different development strategies:a semi-automated process utilizing the AI tools and a traditional manual approach.The results demonstrated a significant reduction in total development time,ranging from 40%to 51%.However,it was observed that the generated content could be inaccurate and incomplete,necessitating review and debugging before being applied to projects.In conclusion,given the increasing shift towards automation in software engineering,further research is critical to enhance the efficiency and reliability of AI tools,particularly those that leverage natural language processing(NLP)technologies.展开更多
Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of softwar...Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of software systems have attracted a tremendous amount of interest in recent years.In this paper,based on the source code of Tar and MySQL,we propose an approach to generate coupled software networks and construct three kinds of directed software networks:The function call network,the weakly coupled network and the strongly coupled network.The structural properties of these complex networks are extensively investigated.It is found that the average influence and the average dependence for all functions are the same.Moreover,eight attacking strategies and two robustness indicators(the weakly connected indicator and the strongly connected indicator)are introduced to analyze the robustness of software networks.This shows that the strongly coupled network is just a weakly connected network rather than a strongly connected one.For MySQL,high in-degree strategy outperforms other attacking strategies when the weakly connected indicator is used.On the other hand,high out-degree strategy is a good choice when the strongly connected indicator is adopted.This work will highlight a better understanding of the structure and robustness of software networks.展开更多
The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study ut...The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.展开更多
This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is ...This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.展开更多
The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfa...The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications.To handle the interfacing complexity problem,this article introduces a Semantic Interfacing Obscuration Model(SIOM)for IoT software-engineered platforms.The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model.Based on the level of obscuration between the infrastructure hardware to the end-user software,the modifications through device replacement,capacity amendments,or interface bug fixes are performed.These modifications are based on the level of semantic obscurations observed during the application service intervals.The obscuration level is determined using knowledge learning as a progression from hardware to software semantics.The results reported were computed using specific metrics obtained from these experimental evaluations:an 8.94%reduction in interfacing complexity and a 15.04%improvement in integration progression.The knowledge of obscurationsmaps themodifications appropriately to reinstate the agility testing of the hardware/software integrations.This modification-based semantics is verified using semantics error,modification time,and complexity.展开更多
Starting with the goal and significance of software security testing,this paper introduces the main methods of software security testing in the open network environment,including formal security testing,white box test...Starting with the goal and significance of software security testing,this paper introduces the main methods of software security testing in the open network environment,including formal security testing,white box testing,fuzzy testing,model testing,and fault injection testing.A software security testing method based on a security target model is proposed.This paper provides new ideas for software security testing,better adapts to the open network environment,improves the efficiency and quality of testing,and builds a good software application environment.展开更多
Quality engineers play a key role in software product development,covering various stages such as requirements analysis,design,coding,testing,and delivery.Its responsibilities include formulating quality standards,wri...Quality engineers play a key role in software product development,covering various stages such as requirements analysis,design,coding,testing,and delivery.Its responsibilities include formulating quality standards,writing test cases,conducting functional and performance tests,and optimizing the product based on feedback.In government procurement projects,quality evaluation focuses on process compliance,security,and functional compatibility.KPI evaluation trees are commonly used for quantitative assessment,and a dynamic adjustment mechanism for indicators needs to be established to cope with complex demands.In addition,risk-driven testing and agile development should be combined to set up quality access control to ensure that each iteration version meets expectations.The multi-dimensional quality assurance and verification scoring mechanism can effectively enhance product reliability and reduce project risks.展开更多
The coordinated regional development strategy,recognized as one of China’s seven development strategies,plays a crucial role in reducing regional development disparities,optimizing resource allocation,and facilitatin...The coordinated regional development strategy,recognized as one of China’s seven development strategies,plays a crucial role in reducing regional development disparities,optimizing resource allocation,and facilitating high-quality development.This study analyzes a total of 418 relevant publications from China spanning the years 1998 to 2022.Utilizing CiteSpace software,a visualization analysis of keyword cooccurrence,mutation,and other bibliometric characteristics was conducted.The findings indicate that the number of publications during the specified period exhibited a fluctuating upward trend,with a notable increase observed after 2018.Furthermore,the research demonstrated a weak interdisciplinary crossover and a low intensity of collaboration among authors.The primary thematic areas of focus were identified as follows:connotation,mechanisms,countermeasure and suggestion,and evaluation.展开更多
Driven by the wave of informatization and intelligence,the smart city has become a new trend of global urban development.The intelligent transformation of energy systems is of great importance to a smart city.The Inte...Driven by the wave of informatization and intelligence,the smart city has become a new trend of global urban development.The intelligent transformation of energy systems is of great importance to a smart city.The Internet helps the sustainable development of smart cities by optimizing resource allocation,improving utilization efficiency,and promoting market competition.This study analyzes the current situation and problems of energy Internet supporting smart cities and finds that policy environment,technology maturity,market demand,and industrial chain integration have a significant positive impact on its development.Based on this,relevant strategies are proposed to provide theoretical and practical guidance for the integrated development of smart cities and the energy Internet.展开更多
基金supported in part by the Northeastern University’s 2024 Undergraduate Education and Teaching Reform Research Project:Innovation and Practice of Professional Course Teaching Paradigms in the Context of Digital Education.
文摘The rapid development of artificial intelligence(AI)has placed significant pressure on universities to rethink how they train software engineering students.Tools like GitHub Copilot can now generate basic code in seconds.This raises important questions:What is the value of traditional programming education?What role should instructors play when AI becomes a powerful teaching assistant?How should the goals of software engineering programs change as companies increasingly use AI to handle coding tasks?This paper explores the key challenges AI brings to software engineering education and proposes practical strategies for updating talent development models to meet these changes.
基金supported by the Research Funding Project for Graduate Education and Teaching Reform of Beijing University of Posts and Telecommunications(No.2024Y036)the Postgraduate Education and Teaching Reform Research Fund Project of Beijing University of Posts and Telecommunications(No.2024Z007)the Postgraduate Education and Teaching Reform Project of Beijing University of Posts and Telecommunications(2025).
文摘Traditional grade-centered evaluation models are inadequate for high-quality software engineering talents in the digital and AI era.This study develops an academic development monitoring system to address shortcomings in dynamics,interdisciplinary integration,and industry adaptability.It builds a multi-dimensional dynamic model covering seven core dimensions with quantitative scoring,non-linear weighting,and DivClust grouping.An intelligent platform with real-time monitoring,early warning,and personalized recommendations integrates AI like multi-modal fusion and large-model diagnosis.The“monitoring-warning-improvement”loop helps optimize training programs,support personalized planning,and bridge talent-industry gaps,enabling digital transformation in software engineering education evaluation.
文摘Advances in Alzheimer's disease(AD)research have deepened our understanding,yet the mechanisms driving its progression remain unclear.Although a range of in vivo biomarkers is now available(e.g.,measurements of amyloidbeta(Aβ)and ta u accumulation-the molecular hallmarks of AD-structural magnetic resonance imaging(MRI),assessments of brain metabolism,and,more recently,blood-based markers),a definitive diagnosis of AD continues to be challenging.For example,Frisoni et al.
基金supported by grants from the Deutsche Forschungsgemeinschaft(DFG)to MW.
文摘Oligodendrocytes and their cell-intrinsic gene regulatory network:Oligodendrocytes(OLs)are the myelinating glial cells of the vertebrate central nervous system.They are responsible for insulating neuronal axons with a lipid-rich myelin sheath,which enables the saltatory conduction of action potentials.During development,oligodendrocyte progenitor cells(OPCs)emerge from neural stem cells in the ventricular zone.They then proliferate,increase their number,and migrate to their final destination where they encounter unmyelinated neuronal axons and differentiate in a stepwise fashion into myelinating oligodendrocytes(mOLs)under the influence of environmental stimuli.
文摘Amid the lingering chill of a Beijing spring during China’s annual Two Sessions,Zheng Wangchun strode into the lounge after finishing the morning’s group discussion.The deputy to the National People’s Congress and secretary of the CPC Gulu Village Branch,better known as Cliff Village,in Hanyuan County,Ya’an City,Sichuan Province,was still dressed in his Yi ethnic waistcoat.
文摘Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our palms.To conduct research in this field,periodic comparative analysis is needed with the new techniques coming up rapidly.The purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way forward.This review follows Kitchenham’s review protocol.The review has been divided into three main stages including planning,execution,and analysis.From the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation techniques.Quantifying risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation efforts.Through a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat landscape.The review reveals that threat analysis and security testing are needed to develop automated tools for the future.Accurate estimation of effort required to prioritize potential security risks is a big challenge in software security.The accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep learning.It is also imperative to validate these effort estimation methods to ensure all potential security threats are addressed.Another challenge is selecting the right model for each specific security threat.To achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.
基金funded by the Youth Fund of the National Natural Science Foundation of China(Grant No.42261070).
文摘Spectrum-based fault localization (SBFL) generates a ranked list of suspicious elements by using the program execution spectrum, but the excessive number of elements ranked in parallel results in low localization accuracy. Most researchers consider intra-class dependencies to improve localization accuracy. However, some studies show that inter-class method call type faults account for more than 20%, which means such methods still have certain limitations. To solve the above problems, this paper proposes a two-phase software fault localization based on relational graph convolutional neural networks (Two-RGCNFL). Firstly, in Phase 1, the method call dependence graph (MCDG) of the program is constructed, the intra-class and inter-class dependencies in MCDG are extracted by using the relational graph convolutional neural network, and the classifier is used to identify the faulty methods. Then, the GraphSMOTE algorithm is improved to alleviate the impact of class imbalance on classification accuracy. Aiming at the problem of parallel ranking of element suspicious values in traditional SBFL technology, in Phase 2, Doc2Vec is used to learn static features, while spectrum information serves as dynamic features. A RankNet model based on siamese multi-layer perceptron is constructed to score and rank statements in the faulty method. This work conducts experiments on 5 real projects of Defects4J benchmark. Experimental results show that, compared with the traditional SBFL technique and two baseline methods, our approach improves the Top-1 accuracy by 262.86%, 29.59% and 53.01%, respectively, which verifies the effectiveness of Two-RGCNFL. Furthermore, this work verifies the importance of inter-class dependencies through ablation experiments.
基金supported by the National Medical Products Administration Commissioned Research Project (No.20211440216)the National Administration of Traditional Chinese Medicine Science and Technology Project (No.GZY-KJS-2024-03)+3 种基金the State Key Laboratory of Drug Regulatory Science Project (No.2023SKLDRS0104)the Basic Research Program Natural Science Fund-Frontier Leading Technology Basic Research Special Project of Jiangsu Province (No.BK20232014)the Programs Foundation for Leading Talents in National Administration of Traditional Chinese Medicine of China“Qihuang scholars”Projectthe Tianjin Administration for Market Regulation Science and Technology Key Projects (No.2022-W35)。
文摘The research and development of new traditional Chinese medicine(TCM)drugs have progressively established a novel system founded on the integration of TCM theory,human experience,and clinical trials(termed the“Three Combinations”).However,considering TCM's distinctive features of“syndrome differentiation and treatment”and“multicomponent formulations and complex mechanisms”,current TCM drug development faces challenges such as insufficient understanding of the material basis and the overall mechanism of action and an incomplete evidence chain system.Moreover,significant obstacles persist in gathering human experience data,evaluating clinical efficacy,and controlling the quality of active ingredients,which impede the innovation process in TCM drug development.Network pharmacology,centered on the“network targets”theory,transcends the limitations of the conventional“single target”reductionist research model.It emphasizes the comprehensive effects of disease or syndrome biological networks as targets to elucidate the overall regulatory mechanism of TCM prescriptions.This approach aligns with the holistic perspective of TCM,offering a novel method consistent with TCM's holistic view for investigating the complex mechanisms of TCM and developing new TCM drugs.It is internationally recognized as a“next-generation drug research model”.To advance the research of new tools,methods,and standards for TCM evaluation and to overcome fundamental,critical,and cutting-edge technical challenges in TCM regulation,this consensus aims to explore the characteristics,progress,challenges,applicable pathways,and specific applications of network pharmacology as a new theory,method,and tool in TCM drug development.The goal is to enhance the quality of TCM drug research and development and accelerate the efficiency of developing new TCM products.
文摘Software-defined networking(SDN)is an innovative paradigm that separates the control and data planes,introducing centralized network control.SDN is increasingly being adopted by Carrier Grade networks,offering enhanced networkmanagement capabilities than those of traditional networks.However,because SDN is designed to ensure high-level service availability,it faces additional challenges.One of themost critical challenges is ensuring efficient detection and recovery from link failures in the data plane.Such failures can significantly impact network performance and lead to service outages,making resiliency a key concern for the effective adoption of SDN.Since 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 SDN.The survey provides a critical comparison of existing failure detection techniques,highlighting their advantages and disadvantages.Additionally,it examines the current failure recovery methods,categorized as either restoration-based or protection-based,and offers a comprehensive comparison of their strengths and limitations.Lastly,future research challenges and directions are discussed to address the shortcomings of existing failure recovery methods.
基金supported in part by the Universityindustry Collaborative Education Program of the Ministry of Education under Grant No.202102383004。
文摘The advancement of Internet of Things(IoT)technology is driving industries toward intelligent digital transformation,highlighting the crucial role of software engineering.Despite this,the integration of software engineering into IoT engineering education remains underexplored.To address this gap,the School of Software at North University of China,in collaboration with QST Innovation Technology Group Co.,Ltd.(QST),has developed an innovative educational mechanism.This initiative focuses on the software engineering IoT track and optimizes the teaching process through the outcome-based education(OBE)concept.It incorporates military-industrial characteristics,introduces advanced information and technology curricula,and enhances laboratory infrastructure.The goal is to cultivate innovative talents with unique capabilities,thereby fostering the comprehensive development and application of IoT technology.
文摘Link failure is a critical issue in large networks and must be effectively addressed.In software-defined networks(SDN),link failure recovery schemes can be categorized into proactive and reactive approaches.Reactive schemes have longer recovery times while proactive schemes provide faster recovery but overwhelm the memory of switches by flow entries.As SDN adoption grows,ensuring efficient recovery from link failures in the data plane becomes crucial.In particular,data center networks(DCNs)demand rapid recovery times and efficient resource utilization to meet carrier-grade requirements.This paper proposes an efficient Decentralized Failure Recovery(DFR)model for SDNs,meeting recovery time requirements and optimizing switch memory resource consumption.The DFR model enables switches to autonomously reroute traffic upon link failures without involving the controller,achieving fast recovery times while minimizing memory usage.DFR employs the Fast Failover Group in the OpenFlow standard for local recovery without requiring controller communication and utilizes the k-shortest path algorithm to proactively install backup paths,allowing immediate local recovery without controller intervention and enhancing overall network stability and scalability.DFR employs flow entry aggregation techniques to reduce switch memory usage.Instead of matching flow entries to the destination host’s MAC address,DFR matches packets to the destination switch’s MAC address.This reduces the switches’Ternary Content-Addressable Memory(TCAM)consumption.Additionally,DFR modifies Address Resolution Protocol(ARP)replies to provide source hosts with the destination switch’s MAC address,facilitating flow entry aggregation without affecting normal network operations.The performance of DFR is evaluated through the network emulator Mininet 2.3.1 and Ryu 3.1 as SDN controller.For different number of active flows,number of hosts per edge switch,and different network sizes,the proposed model outperformed various failure recovery models:restoration-based,protection by flow entries,protection by group entries and protection by Vlan-tagging model in terms of recovery time,switch memory consumption and controller overhead which represented the number of flow entry updates to recover from the failure.Experimental results demonstrate that DFR achieves recovery times under 20 milliseconds,satisfying carrier-grade requirements for rapid failure recovery.Additionally,DFR reduces switch memory usage by up to 95%compared to traditional protection methods and minimizes controller load by eliminating the need for controller intervention during failure recovery.Theresults underscore the efficiency and scalability of the DFR model,making it a practical solution for enhancing network resilience in SDN environments.
文摘In recent years,automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market.The integration of artificial intelligence(AI)tools,particularly those using natural language processing(NLP)like ChatGPT,has opened new possibilities for automating various stages of the development lifecycle.The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development.An artificial intelligence(AI)tool was developed using the OpenAI—Application Programming Interface(API),incorporating two key functionalities:1)generating user stories based on case or process inputs,and 2)estimating the effort required to execute each user story.Additionally,ChatGPT was employed to generate application code.The AI tool was tested in three case studies,each explored under two different development strategies:a semi-automated process utilizing the AI tools and a traditional manual approach.The results demonstrated a significant reduction in total development time,ranging from 40%to 51%.However,it was observed that the generated content could be inaccurate and incomplete,necessitating review and debugging before being applied to projects.In conclusion,given the increasing shift towards automation in software engineering,further research is critical to enhance the efficiency and reliability of AI tools,particularly those that leverage natural language processing(NLP)technologies.
基金supported by the Beijing Education Commission Science and Technology Project(No.KM201811417005)the National Natural Science Foundation of China(No.62173237)+6 种基金the Aeronautical Science Foundation of China(No.20240055054001)the Open Fund of State Key Laboratory of Satellite Navigation System and Equipment Technology(No.CEPNT2023A01)Joint Fund of Ministry of Natural Resources Key Laboratory of Spatiotemporal Perception and Intelligent Processing(No.232203)the Civil Aviation Flight Technology and Flight Safety Engineering Technology Research Center of Sichuan(No.GY2024-02B)the Applied Basic Research Programs of Liaoning Province(No.2025JH2/101300011)the General Project of Liaoning Provincial Education Department(No.20250054)Research on Safety Intelligent Management Technology and Systems for Mixed Operations of General Aviation Aircraft in Low-Altitude Airspace(No.310125011).
文摘Software systems play increasing important roles in modern society,and the ability against attacks is of great practical importance to crucial software systems,resulting in that the structure and robustness of software systems have attracted a tremendous amount of interest in recent years.In this paper,based on the source code of Tar and MySQL,we propose an approach to generate coupled software networks and construct three kinds of directed software networks:The function call network,the weakly coupled network and the strongly coupled network.The structural properties of these complex networks are extensively investigated.It is found that the average influence and the average dependence for all functions are the same.Moreover,eight attacking strategies and two robustness indicators(the weakly connected indicator and the strongly connected indicator)are introduced to analyze the robustness of software networks.This shows that the strongly coupled network is just a weakly connected network rather than a strongly connected one.For MySQL,high in-degree strategy outperforms other attacking strategies when the weakly connected indicator is used.On the other hand,high out-degree strategy is a good choice when the strongly connected indicator is adopted.This work will highlight a better understanding of the structure and robustness of software networks.
基金research supported wholly by the National Research Foundation (NRF) of South Africathe Dutch Research Council (NWO) Project (UID 129352)
文摘The use ofrenewable energyisan important way toachieve sustainable agriculturalandeconomic development.However,there are differences in accessto renewable energy between the Global North and Global South.This study utilisedan autoregressive distributed lag-error correctionmodel and thedata spanning from 1991to 2021 to comparatively analyse the dynamic relationship amongrenewable energy consumption,the value of agricultural production,gross domestic product(GDP),economic diversificationindex,urban population,the total water extraction for agricultural withdrawal,and trade balancein the Netherlands and South Africa.In the shortrun,renewable energy consumption was increased by the value of agricultural productionbut decreased by GDPin South Africa.In the longrun,renewable energy consumption and GDP increased the value of agricultural production,while the value of agricultural production also increased GDP in South Africa.However,in the Netherlands,there was no short-and long-run relationship betweenrenewable energy consumption and agricultural and economic development.The results revealedthat there was a short-and long-run relationship in South Africa.Moreover,in the Netherlands,the adjustment speed was-1.46 forrenewable energy consumption with an error correction of 0.68 a(8.22 months).In South Africa,the adjustment speedwas-1.28 forrenewable energy consumption with an error correction of 0.78 a(9.38 months).Therefore,compared to South Africa,renewable energy consumptionin the Netherlands takes less time to return to balance after a shock.Thesefindings signify different trajectories on sectoral and economic transition initiatives spurred usingrenewable energy between the Netherlands and South Africa.Policy relating to initiatives such as“agro-energy communities”in Global South countries such as South Africa should be emphasised to promote the use of renewable energy in the agricultural sector.
文摘This paper presents our endeavors in developing the large-scale, ultra-high-resolution E3SM Land Model (uELM), specifically designed for exascale computers furnished with accelerators such as Nvidia GPUs. The uELM is a sophisticated code that substantially relies on High-Performance Computing (HPC) environments, necessitating particular machine and software configurations. To facilitate community-based uELM developments employing GPUs, we have created a portable, standalone software environment preconfigured with uELM input datasets, simulation cases, and source code. This environment, utilizing Docker, encompasses all essential code, libraries, and system software for uELM development on GPUs. It also features a functional unit test framework and an offline model testbed for comprehensive numerical experiments. From a technical perspective, the paper discusses GPU-ready container generations, uELM code management, and input data distribution across computational platforms. Lastly, the paper demonstrates the use of environment for functional unit testing, end-to-end simulation on CPUs and GPUs, and collaborative code development.
文摘The agility of Internet of Things(IoT)software engineering is benchmarked based on its systematic insights for wide application support infrastructure developments.Such developments are focused on reducing the interfacing complexity with heterogeneous devices through applications.To handle the interfacing complexity problem,this article introduces a Semantic Interfacing Obscuration Model(SIOM)for IoT software-engineered platforms.The interfacing obscuration between heterogeneous devices and application interfaces from the testing to real-time validations is accounted for in this model.Based on the level of obscuration between the infrastructure hardware to the end-user software,the modifications through device replacement,capacity amendments,or interface bug fixes are performed.These modifications are based on the level of semantic obscurations observed during the application service intervals.The obscuration level is determined using knowledge learning as a progression from hardware to software semantics.The results reported were computed using specific metrics obtained from these experimental evaluations:an 8.94%reduction in interfacing complexity and a 15.04%improvement in integration progression.The knowledge of obscurationsmaps themodifications appropriately to reinstate the agility testing of the hardware/software integrations.This modification-based semantics is verified using semantics error,modification time,and complexity.
文摘Starting with the goal and significance of software security testing,this paper introduces the main methods of software security testing in the open network environment,including formal security testing,white box testing,fuzzy testing,model testing,and fault injection testing.A software security testing method based on a security target model is proposed.This paper provides new ideas for software security testing,better adapts to the open network environment,improves the efficiency and quality of testing,and builds a good software application environment.
文摘Quality engineers play a key role in software product development,covering various stages such as requirements analysis,design,coding,testing,and delivery.Its responsibilities include formulating quality standards,writing test cases,conducting functional and performance tests,and optimizing the product based on feedback.In government procurement projects,quality evaluation focuses on process compliance,security,and functional compatibility.KPI evaluation trees are commonly used for quantitative assessment,and a dynamic adjustment mechanism for indicators needs to be established to cope with complex demands.In addition,risk-driven testing and agile development should be combined to set up quality access control to ensure that each iteration version meets expectations.The multi-dimensional quality assurance and verification scoring mechanism can effectively enhance product reliability and reduce project risks.
文摘The coordinated regional development strategy,recognized as one of China’s seven development strategies,plays a crucial role in reducing regional development disparities,optimizing resource allocation,and facilitating high-quality development.This study analyzes a total of 418 relevant publications from China spanning the years 1998 to 2022.Utilizing CiteSpace software,a visualization analysis of keyword cooccurrence,mutation,and other bibliometric characteristics was conducted.The findings indicate that the number of publications during the specified period exhibited a fluctuating upward trend,with a notable increase observed after 2018.Furthermore,the research demonstrated a weak interdisciplinary crossover and a low intensity of collaboration among authors.The primary thematic areas of focus were identified as follows:connotation,mechanisms,countermeasure and suggestion,and evaluation.
基金Research and Innovation Team Building Project of Qingdao City University(QCU23TDKJO1)。
文摘Driven by the wave of informatization and intelligence,the smart city has become a new trend of global urban development.The intelligent transformation of energy systems is of great importance to a smart city.The Internet helps the sustainable development of smart cities by optimizing resource allocation,improving utilization efficiency,and promoting market competition.This study analyzes the current situation and problems of energy Internet supporting smart cities and finds that policy environment,technology maturity,market demand,and industrial chain integration have a significant positive impact on its development.Based on this,relevant strategies are proposed to provide theoretical and practical guidance for the integrated development of smart cities and the energy Internet.
