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The complexity nature of large-scale software systems 认领 引用 被引量：1
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作者 闫栋 祁国宁 顾新建 《Chinese Physics B》 CAS 2006年第11期2489-2495,共7页
In software engineering, class diagrams are often used to describe the system＇s class structures in Unified Modelling Language （UML）. A class diagram, as a graph, is a collection of static declarative model element... In software engineering, class diagrams are often used to describe the system＇s class structures in Unified Modelling Language （UML）. A class diagram, as a graph, is a collection of static declarative model elements, such as classes, interfaces, and the relationships of their connections with each other. In this paper, class graphs axe examined within several Java software systems provided by Sun and IBM, and some new features are found. For a large-scale Java software system, its in-degree distribution tends to an exponential distribution, while its out-degree and degree distributions reveal the power-law behaviour. And then a directed preferential-random model is established to describe the corresponding degree distribution features and evolve large-scale Java software systems. 展开更多
关键词 software system degree distribution power-law behaviour exponential distribution
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Visualization Analysis Framework for Large-Scale Software Based on Software Network 认领 引用
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作者 Shengbing Ren Mengyu Jia +1 位作者 Fei Huang Yuan Liu 《国际计算机前沿大会会议论文集》 EI 2017年第1期185-187,共3页
Large-scale software systems,which are the most sophisticated human-designed objects,play more and more important role in our daily life.Consequently effective analysis for large-scale software has become an urgent pr... Large-scale software systems,which are the most sophisticated human-designed objects,play more and more important role in our daily life.Consequently effective analysis for large-scale software has become an urgent problem to be solved with the increasing issues of software security and the continuous expansion of software applications scope.For the characteristics of large scale and complex structure in large-scale software,the traditional software analysis techniques are difficult to be used.With the problem of difficulty in presentation,storage and low efficiency in the process of large-scale software analysis,the visualization analysis framework for large-scale software based on software network,named SoNet,is proposed with the combination of complex network theory and program slicing technique.Constraint logic attributes of the programs will be obtained through source code parsing.Then we will construct a global view by the theory of complex network after extracting software structure and behavior,improving user’s perception of software architecture in a macro perspective.Use case slicing will be realized combined with Redis cluster,and accessibility analysis when given a keyword to be analyzed.We evaluate our prototype implementation on an open source software project named SoundSea in Github,and the results suggest that our approach can realize the analysis for large-scale software. 展开更多
关键词 Large-scale software Software network Visualization Constraint logic
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Application of Design Patterns in Process of Large-Scale Software Evolving 认领 引用
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作者 Wei WANG Hai ZHAO +7 位作者 Hui LI Peng LI Dong YAO Zheng LIU Bo LI Shuang YU Hong LIU Kunzhan YANG 《Journal of Software Engineering and Applications》 2010年第1期58-64,共7页
To search for the Design Patterns’ influence on the software, the paper abstracts the feature models of 9 kinds of classic exiting design patterns among the 23 kinds and describes the features with algorithm language... To search for the Design Patterns’ influence on the software, the paper abstracts the feature models of 9 kinds of classic exiting design patterns among the 23 kinds and describes the features with algorithm language. Meanwhile, searching for the specific structure features in the network, the paper designs 9 matching algorithms of the 9 kinds design patterns mentioned above to research on the structure of the design patterns in the software network. At last, the paper analyzes the evolving trends of the software scale and the application frequency of the 9 kinds of design patterns as the software evolves, and search for the rules how these design patterns are applied into 4 kinds of typical software. 展开更多
关键词 Design Pattern Feature Model Software Network Evolving Trends
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FURobot:A software control platform for construction robots for large-scale construction 认领 引用 被引量：1
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作者 LU Ming Philip F.YUAN 《土木与环境工程学报（中英文）》 CSCD 北大核心 2025年第5期1-11,共11页
The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have bec... The advent of parametric design has resulted in a marked increase in the complexity of building.Unfortunately,traditional construction methods make it difficult to meet the needs.Therefore,construction robots have become a pivotal production tool in this context.Since the arm span of a single robot usually does not exceed 3 meters,it is not competent for producing large-scale building components.Accordingly,the extension of the robot,s working range is often achieved by external axes.Nevertheless,the coupling control of external axes and robots and their kinematic solution have become key challenges.The primary technical difficulties include customized construction robots,automatic solutions for external axes,fixed axis joints,and specific motion mode control.This paper proposes solutions to these difficulties,introduces the relevant basic concepts and algorithms in detail,and encapsulates these robotics principles and algorithm processes into the Grasshopper plug-in commonly used by architects to form the FURobot software platform.This platform effectively solves the above problems,lowers the threshold for architects,and improves production efficiency.The effectiveness of the algorithm and software in this paper is verified through simulation experiments. 展开更多
关键词 construction robots customization construction robotics kinematics software
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OPFEM:architectural design and implementation of a CAE software for finite element modeling and simulation 认领 引用
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作者 Wei Huang Qun Huang +3 位作者 Jie Yang Xiaowei Bai Tianyun He Heng Hu 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第2期264-333,共70页
To address challenges in architectural extensibility and cross-module collaboration of CAE software,this study proposes OPFEM(open-source Python-based finite element modeling)—an open-source framework featuring a uni... To address challenges in architectural extensibility and cross-module collaboration of CAE software,this study proposes OPFEM(open-source Python-based finite element modeling)—an open-source framework featuring a unified four-layer architecture.The geometric modeling framework achieves plug-in support for geometric kernels through an interface abstraction layer and adapter patterns,decoupling kernel-specific implementations while enabling state machine-driven interaction design and parametric sketching.The pre-processing modules establish multi-level associations among materials,sections,and geometric entities using Composite and Factory patterns,while implementing Observer pattern to ensure geometric-mesh consistency and employing finite-state machines to optimize boundary workflows.The computational modules implement a modular finite element library that decouples topology from element attributes,along with a surface boundary element technique for load conversion and task-scheduling management,validated through a cantilever beam large-deformation case.The post-processing module facilitates standardized data storage and dynamic field visualization through architecture-level standardized interface definitions and hierarchical component design.Collectively,OPFEM achieves full-process integration from parametric modeling to nonlinear solving and visualization,enhancing configuration efficiency and providing an extensible,pattern-driven solution for complex CAE challenges. 展开更多
关键词 Finite element method CAE software architecture Object-oriented programming Modular design Opensource software
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Software and layout optimization of HIRFL-CSR external-target experiment 认领 引用
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作者 Jian-Wang Hong Chen-Lu Hu +29 位作者 Yu-Hong Yu Nu Xu Zhi-Yu Sun Hao Qiu Zhi-Gang Xiao Ming Shao Li-Min Duan Xiong-Hong He Zhi-Hui Xu Yi Wang Dong Han Zi-Xuan Chen Feng-Yi Zhao He-Run Yang Xiang-Lun Wei Rong-Jiang Hu Feng Liu Hua Pei Ya-Ping Wang Ye Tian Zhi Qin Dong-Dong Hu Guo-Dong Shen Li-Jun Mao Wei Wu Wei You Yu-Quan Chen Peng Yang De-Qing Fang Ya-Peng Zhang 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2026年第5期289-297,共9页
Heavy-ion collisions(HICs)is a unique experimental tool for investigating the properties of nuclear matter under extreme conditions in the laboratory.At HIRFL-CSR energies,HICs can create nuclear matter with 2-3 times... Heavy-ion collisions(HICs)is a unique experimental tool for investigating the properties of nuclear matter under extreme conditions in the laboratory.At HIRFL-CSR energies,HICs can create nuclear matter with 2-3 times the saturation density(ρ0).The HIRFL-CSR external-target experiment(CEE)is a large-acceptance spectrometer designed to explore frontier topics in high-energy nuclear physics,such as the QCD phase structure and nuclear matter equation of states.In this letter,we introduce simulation and analysis software for the CEE experiment(CeeROOT).Based on the CEE conceptual design and CeeROOT software,the configurations of its subdetectors were optimized by considering foreseeable physical constraints.The final detector layout of the CEE spectrometer and its acceptances were validated through simulations of U+U collisions at 500 MeV/u and pp collisions at 2.8 GeV,which demonstrated that the CEE experiment will serve as a detector with wide acceptance and multi-particle identification capabilities for studying high-energy nuclear physics topics at HIRFL-CSR energies with pp,pA,and A A collisions. 展开更多
关键词 CEE experiment Simulation software Optimization HIRFL-CSR
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Large-scale physical simulation of flow behavior in Kelasu ultra-deep fractured low-porosity sandstone gas reservoirs 认领 引用
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作者 Yong-Liang Tang Jun Yao +5 位作者 Xue-Hao Pei Dong Chen Yong-Bin Zhang Feng-Lai Yang Xu Zhou Zhao-Qin Huang 《Petroleum Science》 SCIE EI CAS CSCD 2026年第3期1360-1370,共11页
The ultra-deep fractured low-porosity sandstone gas reservoirs in the Kuqa Depression of the Tarim Basin exhibit complex characteristics,including high temperature,high pressure,significant in-situ stress,multi-scale ... The ultra-deep fractured low-porosity sandstone gas reservoirs in the Kuqa Depression of the Tarim Basin exhibit complex characteristics,including high temperature,high pressure,significant in-situ stress,multi-scale fractures,and strong aquifer activity.The development of these reservoirs is challenged by rapid water invasion,which causes severe production declines.Conventional experiments fail to adequately simulate the coupled flow between the in-situ matrix and fractures.This study developed a high-temperature,high-pressure large-scale physical simulation platform and a methodology for preparing large rock samples with complex fractures.Using this platform,we conducted single-phase and gas-water two-phase flow experiments under in-situ conditions.The key results indicate that during single-phase depletion,cumulative gas production rapidly reaches a quasi-steady state,confirming the hierarchical flow and coupling from“large fracture”to“small fracture”to“matrix”.The matrix’s gas supply capacity diminishes with decreasing pressure,exacerbating the supply-production imbalance.Constant-volume bottom water experiments reveal that when fracture water saturation exceeds a critical threshold,the matrix gas supply abruptly declines due to“water-sealed gas”.Continuous fracture drainage and pressure reduction can partially alleviate this sealing and restore some gas supply,although recovery remains limited.Experiments under different management strategies demonstrate that higher production rates and larger water-to-gas volume ratios lead to lower cumulative gas production before water sealing,higher abandonment pressures,greater challenges in post-sealing recovery,and consequently,lower ultimate recovery.These findings provide critical insights for optimizing development strategies in ultra-deep fractured low-porosity sandstone gas reservoirs. 展开更多
关键词 Fractured low-porosity sandstone Large-scale physical simulation Multi-scale fractures Gas-water two-phase flow
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Improvement of a Large-Scale Circulation Simulation in an Ocean-Sea-Ice Model with High Resolution 认领 引用
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作者 Yiwen LI Hailong LIU +2 位作者 Pengfei LIN Mengrong Ding Zipeng YU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第6期1270-1290,共21页
The impact of resolution on the large-scale features in an ocean-sea ice coupled model(CAS-LICOM3)is communicated in this paper through three aspects.First,a refined resolution accelerates temperature and salinity dri... The impact of resolution on the large-scale features in an ocean-sea ice coupled model(CAS-LICOM3)is communicated in this paper through three aspects.First,a refined resolution accelerates temperature and salinity drifts at a basin-averaged scale by facilitating exchanges among basins,subsequently reducing global-averaged drifts.This amplification of basin-scale exchanges is associated with an accelerated large-scale circulation,leading to a more rapid equilibration of temperature and salinity near 200 meters.Second,the refined resolution yields improved simulations of large-scale temperature,salinity,and currents,particularly evident in regions such as the Gulf Stream and its extension.Positive feedback mechanisms,such as improved undercurrents and a stronger Atlantic Meridional Ocean Circulation(AMOC),enhance temperature and salinity distributions,further improving the large-scale circulation.Subsurface improvements near 300 m are linked to improved simulations of equatorial undercurrents,Gulf Stream dynamics,and the Deep Western Boundary Current,leading to a more realistic representation of AMOC and high-latitude deep-water formation.However,limitations in vertical resolution may obscure finer-scale improvements in subsurface and deep-ocean processes.Despite having little impact on the temporal variability of phenomena such as ENSO,Indian Ocean Dipole(IOD),PDO,and AMO,the refined resolution enhances the strengths of their variabilities. 展开更多
关键词 refined resolution ocean-sea ice coupled model large-scale circulation climate variability
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A high-performance parallel algorithm based on problem independent machine learning(PIML)for large-scale topology optimization 认领 引用
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作者 Xinyu Ma Mengcheng Huang +4 位作者 Zongliang Du Yilin Guo Chang Liu Yue Mei Xu Guo 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第3期197-213,共17页
Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integra... Although supplying extensive design space,the curse of dimensionality restricts the widespread application of largescale topology optimization in practical engineering.Various acceleration techniques have been integrated with topology optimization,achieving significant attention and progress in large-scale problems.This work aims to investigate how much benefit can be obtained by combining parallel computing and machine learning techniques to enhance the efficiency of large-scale topology optimization algorithms.Accordingly,a parallel problem independent machine learning(PIML)-enhanced topology optimization method is proposed.The PIML model substantially reduces the dimension of the condensed stiffness matrix and its computational cost,and parallel computing reduces the workload per process and enables the application of a parallel multigrid solver.Besides,several techniques,such as matrix-free implementation,direct condensation of uniform coarse elements,and adjusting computational resource limits,have been developed to enhance computational efficiency.The weak scaling efficiency,strong scaling speedup,and maximum achievable efficiency of the proposed method are validated across multiple numerical examples,showing significant improvement in the tractable problem size and solution efficiency compared to traditional topology optimization algorithms. 展开更多
关键词 Topology optimization Large-scale Problem independent machine learning(PIML) Parallel computing
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Investigation and prediction of material transfer in transitional region under local loading forming of large-scale rib-web components from perspective of multi-stage stress states 认领 引用
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作者 Chao YANG Ke WEI +2 位作者 Fangbin WANG Yong HOU Wenzhen CHEN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期695-713,共19页
Titanium alloy large-scale rib-web components,known for their lightweight and highstrength properties,have the potential to substantially lighten the load-bearing components of aircraft.Isothermal Local Loading(ILL)ha... Titanium alloy large-scale rib-web components,known for their lightweight and highstrength properties,have the potential to substantially lighten the load-bearing components of aircraft.Isothermal Local Loading(ILL)has been recognized as an advanced technique for the integrated and less-loading forming of these components.However,material transfer in the transitional region during ILL often leads to folding defect near the die-partition line.To this end,the position of the neutral layer during ILL is calculated via the slab method,which is modified to align with the material flow in the transitional region,taking into account the multi-stage stress states under diverse boundary conditions.By utilizing this calculation model,the material transfer rate and rib-groove filling height can be ascertained.The material transfer rate serves as a criterion for predicting folding defect,and thereby an optimal billet is obtained and implemented in the ILL process.The results demonstrate that the material transfer rate is significantly decreased compared to the non-optimized billet,resulting in a non-folding component of transitional region. 展开更多
关键词 Isothermal local loading Large-scale rib-web component Multi-stage stress states Slab method Transitional region
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Two Unconventional Types of Large-scale Circulation Anomalies Inducing Heavy Rainfall over the Yangtze River Basin 认领 引用
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作者 Xinyu LI Mengyao CHEN Riyu LU 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2026年第3期565-577,共13页
Summer rainfall in the Yangtze River basin(YRB)is favored by two key factors in the lower troposphere:the tropical anticyclonic anomaly over the western North Pacific and the extratropical northeasterly anomalies to t... Summer rainfall in the Yangtze River basin(YRB)is favored by two key factors in the lower troposphere:the tropical anticyclonic anomaly over the western North Pacific and the extratropical northeasterly anomalies to the north of the YRB.This study,however,found that approximately 46%of heavy rainfall events in the YRB occur when only one factor appears and the other is opposite signed.Accordingly,these heavy rainfall events can be categorized into two types:the extratropical northeasterly anomalies but tropical cyclonic anomaly(first unconventional type),and the tropical anticyclonic anomaly but extratropical southwesterly anomalies(second unconventional type).Anomalous water vapor convergence and upward motion exists for both types,but through different mechanisms.For the first type,the moisture convergence and upward motion are induced by a cyclonic anomaly over the YRB,which appears in the mid and lower troposphere and originates from the upstream region.For the second type,a mid-tropospheric cyclonic anomaly over Lake Baikal extends southward and results in southwesterly anomalies over the YRB,in conjunction with the tropical anticyclonic anomaly.The southwesterly anomalies transport water vapor to the YRB and lead to upward motion through warm advection.This study emphasizes the role of mid-tropospheric circulations in inducing heavy rainfall in the YRB. 展开更多
关键词 Yangtze River basin heavy rainfall large-scale circulation anomalies
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Large-scale PM2.5 removal and CO2 direct air capture to mitigate ambient air pollution and combat global climate change 认领 引用
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作者 David Y.H.Pui Qingfeng Cao +2 位作者 Thomas Kuehn Charles Lo Sheng-Chieh Chen 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第8期37-47,共11页
This paper summarizes a decade of development of a Solar-Assisted Large-Scale Cleaning System(SALSCS)aimed at mitigating urban PM2.5.This effort has led to the construction and operation of four SALSCS units locate... This paper summarizes a decade of development of a Solar-Assisted Large-Scale Cleaning System(SALSCS)aimed at mitigating urban PM2.5.This effort has led to the construction and operation of four SALSCS units located in Xi'an(China),Yancheng(China),and New Delhi(India).Six papers have been published to document the modeling,design,construction,operation,and measurement of three generations of SALSCSs.The Weather Research and Forecasting(WRF)model was utilized to obtain local meteorological information and solar intensity conditions around the SALSCS.Reynolds-Averaged Navier-Stokes(RANS)simulations and Large Eddy Simulation(LES)have been employed to study the flow patterns and clean air concentration profiles near the units.The first generation SALSCS(Xi'an)takes the form of an updraft solar tower that utilizes solar heating to drive a large volume of air flow through the SALSCS.Filters are positioned along the flow path to remove PM2.5,resulting in cleaner air exiting the top of the tower.In the second generation SALSCS(Yancheng),the media filters are replaced with water spray to scrub out PM2.5.The third generation SALSCS(New Delhi)employs a set of fans to draw PM2.5 from the tower inlet through prefilters and final filters,blowing the cleaned air out near ground level to pedestrians surrounding the SALSCS.A proposal is presented that combines the 1st and 2nd Generation SALSCSs equipped with solar panels and direct air capture(DAC)of CO2 to achieve energy self-sufficiency and large-scale capture of 100 million tons of CO2 annually(100 Mt CO2/yr). 展开更多
关键词 PM2.5 CO2 Global climate change Solar-assisted large-scale cleaning system Direct air capture Sustainability
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QIMIG:A Quantum-Inspired Evolutionary Framework for Software Library Migration 认领 引用
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作者 Yun Liu Jinghua Zhao +3 位作者 Liang Ma Zijie Huang Lizhi Cai Jianxin Ge 《Computers, Materials & Continua》 SCIE EI 2026年第9期795-812,共18页
Automated library migration reduces refactoring costs but challenges traditional evolutionary algorithms,which often suffer from premature convergence and poor recall in sparse,complex API mapping spaces.To address th... Automated library migration reduces refactoring costs but challenges traditional evolutionary algorithms,which often suffer from premature convergence and poor recall in sparse,complex API mapping spaces.To address this,we propose QIMIG,a multi-objective optimization framework integrating quantum-inspired encoding with quality-aware and greedy heuristic filtering.QIMIG utilizes a probabilistic Q-bit representation to maintain population diversity and avoid local optima.Simultaneously,its heuristic components leverage historical usage context to filter semantic noise and guide the search toward valid mappings.Evaluated on 9 real-world migration rules derived from 57,447 open-source projects,QIMIG statistically significantly outperforms state-of-the-art baselines such as UNSGA-III.The framework achieves a global mean F1-score of 0.92,exceeding the best-performing baseline by an absolute margin of 0.05,and demonstrates strong stability in resolving complex mapping structures. 展开更多
关键词 Library migration API mapping search-based software engineering quantum-inspired evolutionary algorithm multi-objective optimization
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Methods,Algorithms,Codes,and Software for Theoretical and Computational Chemistry 认领 引用
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作者 Bin Jiang 《Chinese Journal of Chemical Physics》 SCIE EI CAS CSCD 2026年第3期301-302,共2页
Theoretical and computational chemistry has profoundly impacted a wide range of disciplines,from chemistry and physics to biology and materials science.In recent years,remarkable advances in electronic structure theor... Theoretical and computational chemistry has profoundly impacted a wide range of disciplines,from chemistry and physics to biology and materials science.In recent years,remarkable advances in electronic structure theory,molecular dynamics,and machine learning methods——coupled with increasingly powerful algorithms and software—have equipped chemists with an unprecedented arsenal of tools to tackle complex chemical problems. 展开更多
关键词 theoretical computational chemistry electronic structure theorymolecular dynamicsand algorithms codes software methods materials sciencein theoretical chemistry
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Hierarchical algorithm for large-scale irregular packing problems 认领 引用
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作者 Xiao LIU 《ENGINEERING Information Technology & Electronic Engineering》 SCIE EI CSCD 2026年第3期69-80,共12页
To address the challenge of large-scale packing problems,this paper proposes a novel hierarchical algorithm based on the geometrical classification of parts.The algorithm begins by classifying parts into three levels ... To address the challenge of large-scale packing problems,this paper proposes a novel hierarchical algorithm based on the geometrical classification of parts.The algorithm begins by classifying parts into three levels based on their area and fullness and then applies distinct packing strategies to each category.An innovative“shape matching”method is introduced,which,together with the“box stacking”(for rectangular parts)and“gravity packing,”forms a comprehensive hierarchical packing system.Level-1 comprises large rectangular parts,which are arranged using the box stacking algorithm.By aligning the corner points of the parts’bounding boxes,this method avoids the hooking issue commonly encountered in gravity packing.Level-2 includes both large,irregular parts and medium-sized parts.They are first processed using the shape matching algorithm,where rotation and translation are applied to achieve contour complementarity.The quality of the match is evaluated using the shape matching coefficient(SMC).If the SMC fails to reach the preset quality threshold,the system switches to box stacking(for large,irregular parts)or gravity packing(for medium-sized parts).Level-3 comprises the remaining smaller parts and those that failed to pack in the previous two levels.For these parts,shape matching is attempted first,and the system resorts to gravity packing in case of failure.The experimental and comparative results demonstrate that the proposed hierarchical algorithm achieves higher material utilization than the traditional gravity packing algorithm.This improvement is facilitated by the box stacking and shape matching strategies,which promote a more orderly and compact arrangement of parts. 展开更多
关键词 Large-scale packing Hierarchical algorithm Box stacking Shape matching Gravity packing Principle of minimum potential energy
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Software-hardware co-design accelerates materials simulations 认领 引用
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作者 Xiaozhe Wang Wei Zhang En Ma 《Journal of Semiconductors》 EI CAS CSCD 2026年第7期28-31,共4页
Accurate atomistic and electronic-structure calculations based on density functional theory(DFT)and DFT-based ab initio molecular dynamics(AIMD)calculations underpin much of modern computational chemistry and material... Accurate atomistic and electronic-structure calculations based on density functional theory(DFT)and DFT-based ab initio molecular dynamics(AIMD)calculations underpin much of modern computational chemistry and materials science[1].DFT calculations offer quantitative insights into chemical bonding,charge transport,phase stability,reaction pathways,etc[2]. 展开更多
关键词 chemical bondingcharge software hardware co design density functional theory dft dft based ab initio molecular dynamics ab initio molecular dynamics aimd calculations materials simulations materials science density functional theory
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Predicting Software Security Bugs Using Machine Learning and Quality Metrics: An Empirical Study 认领 引用
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作者 Mohamed Diouf Elisée Toe +2 位作者 Manel Grichi Haïfa Nakouri Fehmi Jaafar 《Computers, Materials & Continua》 SCIE EI 2026年第6期436-477,共42页
Software security bugs present significant security risks to modern systems,leading to unauthorized access,data breaches,and severe operational and financial consequences.Early prediction of such vulnerabilities is th... Software security bugs present significant security risks to modern systems,leading to unauthorized access,data breaches,and severe operational and financial consequences.Early prediction of such vulnerabilities is therefore essential for strengthening software reliability and reducing remediation costs.This study investigates the extent to which static software quality metrics can identify vulnerable code and evaluates the effectiveness of machine learning models for large-scale security-bug prediction.We analyze a dataset of 338,442 source files,including 33,294 buggy files,collected from seven major open-source ecosystems.These ecosystems include GitHub Security Advisories(GHSA),Python Package Index(PyPI),OSS-Fuzz(Google’s open-source fuzzing service),Node Package Manager(npm),Packagist(the PHP package repository),Apache Maven,and NuGet(the.NET package manager).Using the Open Source Vulnerabilities(OSV)platform,we identify 7685 confirmed security bugs and extract 25 static software quality metrics per file with the Understand analysis tool.We apply five complementary feature-importance techniques and evaluate eleven machine-learning classifiers under a time-series cross-validation protocol.Our analysis reveals three key findings.First,six core metrics consistently show strong associations with the presence of security bugs across all feature-selection methods.Second,buggy files exhibit substantially higher metric values,with medians approximately three times those of non-buggy files,a pattern we term the“3×rule”;Mann-Whitney U tests confirm that these differences are statistically significant.Third,the machine-learning models achieve strong predictive performance,with XGBoost providing the best results(recall=0.82,precision=0.95,Receiver Operating Characteristic-Area Under the Curve(ROC-AUC)=0.91).Based on these findings,we propose data-driven warning and critical thresholds for the most influential metrics to support proactive security assessment.Overall,this work provides large-scale empirical evidence that software quality metrics,combined with machine learning,offer actionable signals for detecting security bugs and for integrating automated vulnerability prediction into software development workflows. 展开更多
关键词 Security bugs vulnerability prediction software metrics machine learning code complexity software quality
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Data-Driven Test Case Prioritization(DD-TCP):A Machine Learning Framework for Intelligent Software Quality Assurance 认领 引用
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作者 Hafiz Arslan Ramzan Kamrul Islam +3 位作者 Md Ahbab Hussain Raiyan Muntasir Monim Sabit Md Asad Sadia Ramzan 《Computers, Materials & Continua》 SCIE EI 2026年第7期1369-1389,共21页
Regression testing of large-scale,data-intensive software systems demands efficient test-case prioritization strategies to detect faults early while minimizing computational cost.Conventional prioritization methods,su... Regression testing of large-scale,data-intensive software systems demands efficient test-case prioritization strategies to detect faults early while minimizing computational cost.Conventional prioritization methods,such as coverage-based and risk-based approaches,lack adaptability to evolving project dynamics and fail to leverage the rich test-execution data accumulated over continuous integration cycles.This study presents a Data-Driven Test-Case Prioritization(DD-TCP)Framework that incorporates statistical and machine-learning techniques to model the relationship between test-case features and historical fault detection outcomes.The framework extracts multidimensional attributes including code-change frequency,dependency metrics,execution duration,and past failure density,which are normalized and embedded into a predictive ranking model based on gradient-boosted decision trees.Test cases are then dynamically reordered using a probabilistic gain function that maximizes early fault detection probability.Comprehensive simulations on representative open-source project datasets and synthetically generated large-scale test suites reveal that the proposed Data-Driven Test-Case Prioritization(DD-TCP)framework consistently achieves superior performance,yielding a 32.4%improvement in Average Percentage of Faults Detected(APFD)and a 27.1%reduction in execution overhead relative to baseline methods.The results demonstrate the feasibility of data-centric intelligence for scalable regression testing and provide an analytical foundation for integrating machine learning into next-generation Software Quality Assurance pipelines. 展开更多
关键词 Data-driven test-case prioritization regression testing software quality assurance machine learning continuous integration fault detection efficiency intelligent software systems
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Bearing capacity of composite tunnel lining in soft rocks:Large-scale model test 认领 引用
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作者 Lan Cui Si Luo +4 位作者 Mingqing Xiao Qian Sheng Junjie Zheng Chen Xu Biting Xie 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2026年第4期2757-2775,共19页
Composite lining is widely used in tunnel engineering due to its high strength and adaptability.For current model tests on tunnels with composite lining,a large geometric similarity scale resulted in a small-scale mod... Composite lining is widely used in tunnel engineering due to its high strength and adaptability.For current model tests on tunnels with composite lining,a large geometric similarity scale resulted in a small-scale model.Failure process and force of supports are difficultto observe and measure.Research exploring the bearing capacity of tunnels with composite lining is also limited.To overcome the above deficiencies,a model test method to investigate the bearing capacity of tunnels with composite lining in soft rock is proposed.A large-scale model test system with a similarity scale of 12.5 is developed.Similar materials of surrounding rock,rock bolt,firstand secondary lining are determined by triaxial test,tensile test,and pull-out test.The monitoring scheme is designed to obtain the stress of the surrounding rock,rock bolt,firstand secondary lining.Model tests for tunnels without lining,with composite lining and with dense composite lining are conducted.Complete loading processes are observed,and the bearing capacities are explored.Displacements and stresses of surrounding rock material are discussed.Evolution variations of axial force of rock bolt,stress distribution of firstand secondary lining for tunnel with composite lining and tunnel with dense composite lining are compared.The effect of rock bolt densificationis investigated.The results indicate that total loads transferring to both firstand secondary lining at any area of tunnel are roughly equivalent.There is a‘mutual balance’effect between axial forces of them.Densificationof rock bolt results in greater axial forces of firstlining and rock bolt but smaller axial force of secondary lining. 展开更多
关键词 Composite lining Large-scale model test Bearing capacity Densification of rock bolt Similar material
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Adaptive event-triggered decentralized control for nonlinear interconnected large-scale systems with actuator failures:a fully actuated system approach 认领 引用
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作者 Yueyao Ye Yanan Qi +2 位作者 Yiyu Feng Xiaofeng Xu Xianfu Zhang 《Control Theory and Technology》 EI CSCD 2026年第1期82-95,共14页
This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the ... This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the design process,we transform the studied system into the form of a fully actuated system through a state transformation.Then,to address the unknown nonlinear functions and actuator fault parameters,we employ neural networks and adaptive estimation techniques,respectively.Moreover,to reduce the control cost and improve the control efficiency,we introduce event-triggered inputs into the control strategy.It is proved by the Lyapunov stability analysis that all signals of the closed-loop system are bounded and the output of system eventually converge to a bounded region.The efficacy of the control approach is ultimately demonstrated via the simulation of an actual machine feeding system. 展开更多
关键词 Nonlinear interconnected large-scale systems Fully actuated system approach Actuator failures Neural networks
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