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Multistrategy Improved Aquila Optimizer for Test Case Prioritization 认领 引用
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作者 Jiali Chen Jiheng Zhang +3 位作者 Xiaojie Chen Chong Zeng Honghui Yi Heming Jia 《Computers, Materials & Continua》 SCIE EI 2026年第8期2328-2362,共35页
Traditional heuristic algorithms often fall into local optima and converge slowly when test case prioritization is addressed in regression testing,making them inadequate for complex real-world scenarios.The Aquila opt... Traditional heuristic algorithms often fall into local optima and converge slowly when test case prioritization is addressed in regression testing,making them inadequate for complex real-world scenarios.The Aquila optimizer,a novel metaheuristic algorithm,demonstrates strong global exploration capability but still faces limitations,including insufficient exploitation capability and slow convergence.To overcome these challenges,a multi-strategy improved chaotic Cauchy inverse cumulative distribution Aquila optimizer for test case prioritization is proposed.First,a logistic–sine–cosine composite chaotic mapping is introduced during the initialization phase of the Aquila optimizer to increase population diversity.Second,the mutated random walk strategy is used to improve global exploration,further enhancing the global search ability of the Aquila optimizer.Moreover,during the narrowed exploration and narrowed exploitation phases,the Cauchy inverse cumulative distribution flight replaces the Lévy flight strategy to reallocate individual positions,strengthening individuals’optimization capability and preventing the algorithm from becoming trapped in local optima.Finally,in the later iteration stage,the specular reflection learning strategy is used to perturb the optimal individual positions and improve the Aquila optimizer’s convergence accuracy and comprehensive optimization performance.Five Java projects were selected from the Defects4J benchmark datasets to conduct comparative experiments with the Aquila optimizer and seven other metaheuristic algorithms.The results demonstrate the effectiveness and superiority of the improved algorithm in test case prioritization.It achieves average improvements of approximately 4.96%in the average percentage of fault detection,3.82%in the average percentage of block coverage,and 5.64%in the average percentage of decision coverage,enabling faster coverage of code blocks and branches.The results provide an efficient priority sorting solution for complex regression testing scenarios. 展开更多
关键词 Heuristic algorithm search-based software engineering(SBSE) Aquila optimizer(AO) test case prioritization(TCP) average percentage of fault detection(APFD) average percentage of block coverage(APBC) average percentage of decision coverage(APDC)
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Fate and risk of pesticides in drinking water:From source to tap using a comprehensive analysis and prioritization approach 认领 引用
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作者 Tingting Yang Feng Ge +5 位作者 Yuan Hong Yixuan Wang Gang Zhou Huimin Chen Ninghui Song Ping Li 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第3期320-329,共10页
Ensuring the quality and safety of drinking water is crucial for public health.Yet our understanding of pesticides contamination and associated in drinking water systems remains incomplete.In this study,we conducted a... Ensuring the quality and safety of drinking water is crucial for public health.Yet our understanding of pesticides contamination and associated in drinking water systems remains incomplete.In this study,we conducted a comprehensive analysis combining target,suspect,and nontarget screening to investigate pesticide presence from source to tap in a drinking water treatment plant in Jiangsu,China.We identified 162 pesticides,including10 transformation products,with a composition of 41.3%herbicides,29%insecticides,and 27.7%fungicides.Triazole fungicides were detected at concentrations up to 281.2 ng/L,while atrazine was the most concentrated pesticide at 153.2 ng/L.Post-treatment,65.6%of pesticides were removed,20.3%were reduced,and 14.1%were retained.Three prohibited pesticides in China,metsulfuron-methyl,monocrotophos,and isofenphos-methyl,were detected in source water,along with 22 endocrine-disrupting pesticides and 25 fluorinated pesticides.No substances with persistence,bioaccumulation,mobility,and toxic(PBMT)properties were identified in household tap water.However,flucycloxuron was identified as a PBT substance,while epoxiconazole was classified as a PMT substance.All Hazard Quotient values for adults,children,and infants were below 1.A prioritization method,considering occurrence,classification,preliminary hazard assessment,and human health risk,identified atrazine,flucycloxuron,and epoxiconazole as the highest risk.This study provides a comprehensive characterization of pesticide distribution and risk throughout the drinking water system,highlighting the need for further research on their occurrence,fate,and risk,and providing essential data to inform pollution control and environmental protection strategies in drinking water systems. 展开更多
关键词 Pesticides Drinking water system Comprehensive analysis strategy Environmental fate Prioritization
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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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A Hybrid Approach to Software Testing Efficiency:Stacked Ensembles and Deep Q-Learning for Test Case Prioritization and Ranking 认领 引用
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作者 Anis Zarrad Thomas Armstrong Jaber Jemai 《Computers, Materials & Continua》 SCIE EI 2026年第3期1726-1746,共21页
Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability.While prioritization selects the most relevant test cases for opti... Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability.While prioritization selects the most relevant test cases for optimal coverage,ranking further refines their execution order to detect critical faults earlier.This study investigates machine learning techniques to enhance both prioritization and ranking,contributing to more effective and efficient testing processes.We first employ advanced feature engineering alongside ensemble models,including Gradient Boosted,Support Vector Machines,Random Forests,and Naive Bayes classifiers to optimize test case prioritization,achieving an accuracy score of 0.98847 and significantly improving the Average Percentage of Fault Detection(APFD).Subsequently,we introduce a deep Q-learning framework combined with a Genetic Algorithm(GA)to refine test case ranking within priority levels.This approach achieves a rank accuracy of 0.9172,demonstrating robust performance despite the increasing computational demands of specialized variation operators.Our findings highlight the effectiveness of stacked ensemble learning and reinforcement learning in optimizing test case prioritization and ranking.This integrated approach improves testing efficiency,reduces late-stage defects,and improves overall software stability.The study provides valuable information for AI-driven testing frameworks,paving the way for more intelligent and adaptive software quality assurance methodologies. 展开更多
关键词 Software testing test case prioritization test case ranking machine learning reinforcement learning deep Q-learning
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Occurrence,spatial distribution,and multicriteria prioritization of current-use herbicides in agricultural surface soils of Chinese mainland 认领 引用
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作者 Jie Hou Lixi Wang +3 位作者 Jinze Wang Liyuan Chen Bingjun Han Wenxin Liu 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2026年第6期152-162,共11页
Herbicides are commonly used in crop production and pose environmental threats.Currently,Chinese researches on herbicide residues in agricultural soils focused on Northeast China,with information lacking for most othe... Herbicides are commonly used in crop production and pose environmental threats.Currently,Chinese researches on herbicide residues in agricultural soils focused on Northeast China,with information lacking for most other major crop-producing regions.In this study,topsoil samples were collected from 391 fields in Chinese mainland,and the concentrations of 33 current-use herbicides and two metabolites were quantified.The results revealed herbicides were commonly found in the farmland topsoil in China.The total concentration of the 35 herbicides(i.e.,Σ35herbicides)ranged from 0.354 to 2694μg/kg.And the atrazine was the most frequently detected herbicide.Herbicide concentrations and compositions varied across 31 provinces.The highest median concentration of theΣ35herbicides was detected in Heilongjiang at 33.7μg/kg,while Xizang had the lowest median concentration(0.514μg/kg).It might be due to regional differences in herbicide application and degradation conditions.Additionally,theΣ35herbicides concentration in the topsoil cultivated with grain(median:13.9μg/kg)was higher than in that cultivated with vegetables(median:3.20μg/kg)and fruits(median:2.05μg/kg,p<0.05),mainly because grains require more herbicide application.Overall,theΣ35herbicides concentration in the topsoil of both mulched(median:11.2μg/kg)and non-mulched(median:8.62μg/kg)farmlands was higher than that in greenhouse farmlands(median:3.11μg/kg,p<0.05),possibly because of the differences in the types and extent of the crops cultivated in these systems.Finally,this study was the first to list ten prioritized herbicides based on measured concentration data in China through a multicriteria approach. 展开更多
关键词 Herbicides in surface soils Spatial differences Crop types Farmland types The multicriteria prioritized method
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Accuracy of machine electrocardiogram interpretation and implementation of a de-prioritization protocol in the emergency department 认领 引用
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作者 Adam K Stanley Isobel Sonksen +2 位作者 Henry Morgan Nicola Hilton Sukhbir Bhullar 《World Journal of Emergency Medicine》 SCIE CAS CSCD 2025年第5期486-487,共2页
Computer analysis of electrocardiograms(ECGs)was introduced more than 50 years ago,with the aim to improve efficiency and clinical workflow.[1,2]However,inaccuracies have been documented in the literature.[3,4]Researc... Computer analysis of electrocardiograms(ECGs)was introduced more than 50 years ago,with the aim to improve efficiency and clinical workflow.[1,2]However,inaccuracies have been documented in the literature.[3,4]Research indicates that emergency department(ED)clinician interruptions occur every 4-10 min,which is significantly more common than in other specialties.[5]This increases the cognitive load and error rates and impacts patient care and clinical effi ciency.[1,2,5]De-prioritization protocols have been introduced in certain centers in the United Kingdom(UK),removing the need for clinician ECG interpretation where ECGs have been interpreted as normal by the machine. 展开更多
关键词 cognitive load de prioritization protocol improve efficiency clinical workflow howeverinaccuracies computer analysis electrocardiograms ecgs computer analysis electrocardiograms machine electrocardiogram interpretation emergency department error rates
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Sub-Watershed Prioritization of Chambal River Basin Using Morphometric and Topo-Hydrological Parameters 认领 引用
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作者 Teja Ram Nitharwal Vipin Chandra Lal +4 位作者 Arun Pratap Mishra Kaushalendra Kumar Karvendu Rashmi Singh Geeta Kumari Ashvini Kumar 《Journal of Environmental & Earth Sciences》 CAS 2025年第5期117-129,共13页
Natural resource management is essential to sustain human well-being and the environment.Water and soil are two of the most important natural resources that require careful management.The western part of India faces m... Natural resource management is essential to sustain human well-being and the environment.Water and soil are two of the most important natural resources that require careful management.The western part of India faces multiple challenges,including climatic variability,soil degradation,water scarcity,deforestation,etc.The basin’s sub-watersheds are delineated and prioritised using the Soil and Water Assessment Tool(SWAT)and Sub Watershed Prioritization Tool(SWPT),respectively,using morphometric and topo-hydrological characteristics,and the sub-watersheds are further ranked using Weighted Sum Analysis(WSA).The findings indicate that SWS19,SWS18,SWS1,SWS17,SWS16,and SWS15,which are drained by the rivers Chambal,Kali Sindh,Mashi,Parbati,Parwan,and Beradi,are highly vulnerable sub-watersheds.By integrating remote sensing,GIS techniques,and quantitative morphometric analysis,parameters such as drainage density,stream frequency,bifurcation ratio,and slope gradient were evaluated.The analysis revealed critical sub-watersheds characterized by steep slopes,high drainage density,and poor vegetation cover,indicating their susceptibility to erosion and runoff.The findings underscore the necessity for targeted soil conservation measures,such as contour bunding,afforestation,and water retention structures.This study highlights the utility of geospatial tools for sustainable watershed management and provides a replicable framework for prioritizing sub-watersheds in similar regions. 展开更多
关键词 Morphometric Analysis Topo-Hydrology Sub-Watershed Prioritization Tool(SWPT) Natural Resource Management Soil and Water Weighted Sum Analysis(WSA) Chambal River Basin
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Prioritization of erosion prone sub-watersheds using morphometric analysis and RUSLE-based approaches:A case of Hare Watershed,Abaya Chamo Sub-basin,Ethiopia 认领 引用
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作者 Tegegn Takele MANA Samuel Dagalo HATIYE 《Journal of Mountain Science》 SCIE CSCD 2025年第2期537-555,共19页
Soil erosion in the Hare watershed led to significant land degradation,water pollution,and reduced agricultural productivity.Despite its effects,very few researchers have used combined morphometric and RUSLE model tec... Soil erosion in the Hare watershed led to significant land degradation,water pollution,and reduced agricultural productivity.Despite its effects,very few researchers have used combined morphometric and RUSLE model techniques to quantify soil erosion and thereby prioritize impacted areas.This work used an automated GIS-based tool(SWPT)to prioritize crucial areas based on topohydrological and morphometric factors and predict soil loss in sub-watersheds using the RUSLE model.Land use/cover data were obtained from Landsat imagery,while slope and morphometric information were extracted from digital elevation data with a resolution of 12.5 m.Soil erodibility was determined using Ethiopian soil maps,and rainfall erosivity was computed using meteorological data.An average annual soil loss of 49 t ha-1 yr-1 was observed in the Hare watershed.Sub-watershed 11 was found to be the most affected,with an average annual soil loss of 85.12 t ha-1 yr-1and a compound parameter value(CPV)of 0.059.Subwatershed 17 has the least amount of soil loss,with 3.67t ha-1 yr-1 and a CPV of 1.32.The study emphasizes the usefulness of integrating RUSLE and morphometric analysis for soil and water conservation planning,suggesting a variety of modeling tools in data-sparse locations to quantify and prioritize erosion-prone areas. 展开更多
关键词 Erosion prioritization GIS-based tool(SWPT) Hare watershed Land degradation Morphometric analysis RUSLE model
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Value-Based Test Case Prioritization for Regression Testing Using Genetic Algorithms 认领 引用 被引量：1
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作者 Farrukh Shahzad Ahmed Awais Majeed Tamim Ahmed Khan 《Computers, Materials & Continua》 SCIE EI 2023年第1期2211-2238,共28页
Test Case Prioritization(TCP)techniques perform better than other regression test optimization techniques including Test Suite Reduction(TSR)and Test Case Selection(TCS).Many TCP techniques are available,and their per... Test Case Prioritization(TCP)techniques perform better than other regression test optimization techniques including Test Suite Reduction(TSR)and Test Case Selection(TCS).Many TCP techniques are available,and their performance is usually measured through a metric Average Percentage of Fault Detection(APFD).This metric is value-neutral because it only works well when all test cases have the same cost,and all faults have the same severity.Using APFD for performance evaluation of test case orders where test cases cost or faults severity varies is prone to produce false results.Therefore,using the right metric for performance evaluation of TCP techniques is very important to get reliable and correct results.In this paper,two value-based TCP techniques have been introduced using Genetic Algorithm(GA)including Value-Cognizant Fault Detection-Based TCP(VCFDB-TCP)and Value-Cognizant Requirements Coverage-Based TCP(VCRCB-TCP).Two novel value-based performance evaluation metrics are also introduced for value-based TCP including Average Percentage of Fault Detection per value(APFDv)and Average Percentage of Requirements Coverage per value(APRCv).Two case studies are performed to validate proposed techniques and performance evaluation metrics.The proposed GA-based techniques outperformed the existing state-of-the-art TCP techniques including Original Order(OO),Reverse Order(REV-O),Random Order(RO),and Greedy algorithm. 展开更多
关键词 Average percentage of fault detection test case prioritization regression testing and value-based testing value-based test case prioritization genetic algorithms
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SWPT:An automated GIS-based tool for prioritization of sub-watersheds based on morphometric and topo-hydrological factors 认领 引用 被引量：7
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作者 Omid Rahmati Mahmood Samadi +7 位作者 Himan Shahabi Ali Azareh Elham Rafiei-Sardooi Hossein Alilou Assefa M.Melesse Biswajeet Pradhan Kamran Chapi Ataollah Shirzadi 《Geoscience Frontiers》 SCIE CAS CSCD 2019年第6期2167-2175,共9页
The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the i... The sub-watershed prioritization is the ranking of different areas of a river basin according to their need to proper planning and management of soil and water resources.Decision makers should optimally allocate the investments to critical sub-watersheds in an economically effective and technically efficient manner.Hence,this study aimed at developing a user-friendly geographic information system(GIS)tool,Sub-Watershed Prioritization Tool(SWPT),using the Python programming language to decrease any possible uncertainty.It used geospatial-statistical techniques for analyzing morphometric and topohydrological factors and automatically identifying critical and priority sub-watersheds.In order to assess the capability and reliability of the SWPT tool,it was successfully applied in a watershed in the Golestan Province,Northern Iran.Historical records of flood and landslide events indicated that the SWPT correctly recognized critical sub-watersheds.It provided a cost-effective approach for prioritization of sub-watersheds.Therefore,the SWPT is practically applicable and replicable to other regions where gauge data is not available for each sub-watershed. 展开更多
关键词 SWPT Watershed prioritization GIS Effective management
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Modified Harris Hawks Optimization Based Test Case Prioritization for Software Testing 认领 引用 被引量：2
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作者 Manar Ahmed Hamza Abdelzahir Abdelmaboud +5 位作者 Souad Larabi-Marie-Sainte Haya Mesfer Alshahrani Mesfer Al Duhayyim Hamza Awad Ibrahim Mohammed Rizwanullah Ishfaq Yaseen 《Computers, Materials & Continua》 SCIE EI 2022年第7期1951-1965,共15页
Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software.But,the quality of test cases has a considerable influence on fault revealing capabi... Generally,software testing is considered as a proficient technique to achieve improvement in quality and reliability of the software.But,the quality of test cases has a considerable influence on fault revealing capability of software testing activity.Test Case Prioritization(TCP)remains a challenging issue since prioritizing test cases is unsatisfactory in terms of Average Percentage of Faults Detected(APFD)and time spent upon execution results.TCP ismainly intended to design a collection of test cases that can accomplish early optimization using preferred characteristics.The studies conducted earlier focused on prioritizing the available test cases in accelerating fault detection rate during software testing.In this aspect,the current study designs aModified Harris Hawks Optimization based TCP(MHHO-TCP)technique for software testing.The aim of the proposed MHHO-TCP technique is to maximize APFD and minimize the overall execution time.In addition,MHHO algorithm is designed to boost the exploration and exploitation abilities of conventional HHO algorithm.In order to validate the enhanced efficiency of MHHO-TCP technique,a wide range of simulations was conducted on different benchmark programs and the results were examined under several aspects.The experimental outcomes highlight the improved efficiency of MHHO-TCP technique over recent approaches under different measures. 展开更多
关键词 Software testing harris hawks optimization test case prioritization apfd execution time metaheuristics
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Diversity,Distribution and Prioritization of Fodder Species for Conservation in Kullu District,Northwestern Himalaya,India 认领 引用 被引量：2
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作者 S. S. Samant Man Singh +1 位作者 Manohar Lal Shreekar Pant 《Journal of Mountain Science》 SCIE 2007年第3期259-274,共16页
In the Indian Himalayan Region predominantly rural in character, livestock is one of the main sources of livelihood and integral part of the economy. Livestock mostly rely on fodder from wild. The diversity, distribut... In the Indian Himalayan Region predominantly rural in character, livestock is one of the main sources of livelihood and integral part of the economy. Livestock mostly rely on fodder from wild. The diversity, distribution, utilization pattern, nativity, endemism, rarity, seasonality of availability, nutritive values, perceived economic values and pressure use index of livestock have not been studied. The present study attempts to enumerate 150 species of fodder representing trees (51 spp.), shrubs (54 spp.) and herbs (45 spp.). Poaceae (19 spp.) and Fabaceae (13 spp.) amongst families and Salix (6 spp.), Ficus, Clematis, and Desmodium (5 spp., each) amongst genera are rich in species. Maximum species were found in the 1801 ~ 2600 m zone, and the remaining two zones showed relatively low diversity. Out of the 150 species, 109 are used in summer, 5 winter and 36 throughout year. During rainy season, mostly grasses are used as fodder. Only 83 species are native to the Himalayan region, one species, Strobilanthus atropuroureus is endemic and 35 species are near endemic. The nutritive values of the fodder species were reviewed, and economic values and status of the species were also assessed. The pressure use index of the species was calculated on the basis of cumulative values of the utilization pattern, altitudinal distribution, availability, status, nativity and endemism. Amongst the species, Grewia oppositifoilia, Morus serrata, Indigofera heterantha, Quercus leucotrichphora, Ulmus villosa, U. wallichiana and Aesculus indica showed highest PUI indicating high preference and pressure. Season wise prioritization of the species for different altitudinal zones has been done. Appropriate strategy and action plan have been suggested for the conservation and management of fodder species. 展开更多
关键词 Diversity utilization native endemic nutritive and economic value pressure use index prioritization conservation Indian Himalayan Region
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Customer Prioritization for Medical Supply Chain During COVID-19 Pandemic 认领 引用 被引量：1
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作者 Iram Mushtaq Muhammad Umer +3 位作者 Muhammad Imran Inzamam Mashood Nasir Ghulam Muhammad Mohammad Shorfuzzaman 《Computers, Materials & Continua》 SCIE EI 2022年第1期59-72,共14页
During COVID-19,the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their dem... During COVID-19,the escalated demand for various pharmaceutical products with the existing production capacity of pharmaceutical companies has stirred the need to prioritize its customers in order to fulfill their demand.This study considers a two-echelon pharmaceutical supply chain considering various pharma-distributors as its suppliers and hospitals,pharmacies,and retail stores as its customers.Previous studies have generally considered a balanced situation in terms of supply and demand whereas this study considers a special situation of COVID-19 pandemic where demand exceeds supply Various criteria have been identified from the literature that influences the selection of customers.A questionnaire has been developed to collect primary data from pharmaceutical suppliers pertaining to customerselection criteria.These criteria have been prioritized with respect to eigenvalues obtained from Principal Component Analysis and also validated with the experts’domain-related knowledge using Analytical Hierarchy Process.Profit potential appeared to be the most important criteria of customer selection followed by trust and service convenience brand loyalty,commitment,brand awareness,brand image,sustainable behavior,and risk.Subsequently,Multi Criteria Decision Analysis has been performed to prioritize the customerselection criteria and customers with respect to selection criteria.Three experts with seven and three and ten years of experience have participated in the study.Findings of the study suggest large hospitals,large pharmacies,and small retail stores are the highly preferred customers.Moreover,findings of prioritization of customer-selection criteria fromboth Principal Component Analysis and Analytical Hierarchy Process are consistent.Furthermore,this study considers the experience of three experts to calculate an aggregate score of priorities to reach an effective decision.Unlike traditional supply chain problems of supplier selection,this study considers a selection of customers and is useful for procurement and supply chain managers to prioritize customers while considering multiple selection criteria. 展开更多
关键词 Pandemic customer prioritization pharmaceutical supply chain principal component analysis multi-criteria decision-making
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A hybrid algorithm based on ILP and genetic algorithm for time-aware test case prioritization 认领 引用 被引量：1
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作者 Sun Jiaze Wang Gang 《Journal of Southeast University(English Edition)》 EI CAS 2018年第1期28-35,共8页
To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number... To solve the problem of time-awarc test case prioritization,a hybrid algorithm composed of integer linear programming and the genetic algorithm(ILP-GA)is proposed.First,the test case suite which cm maximize the number of covered program entities a d satisfy time constraints is selected by integer linea progamming.Secondly,the individual is encoded according to the cover matrices of entities,and the coverage rate of program entities is used as the fitness function and the genetic algorithm is used to prioritize the selected test cases.Five typical open source projects are selected as benchmark programs.Branch and method are selected as program entities,and time constraint percentages a e 25%and 75%.The experimental results show that the ILP-GA convergence has faster speed and better stability than ILP-additional and IP-total in most cases,which contributes to the detection of software defects as early as possible and reduces the software testing costs. 展开更多
关键词 test case prioritization integer linear programming(I LP) genetic algorithm time constraint
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AI-Driven Prioritization and Filtering of Windows Artifacts for Enhanced Digital Forensics 认领 引用
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作者 Juhwan Kim Baehoon Son +1 位作者 Jihyeon Yu Joobeom Yun 《Computers, Materials & Continua》 SCIE EI 2024年第11期3371-3393,共23页
Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the comp... Digital forensics aims to uncover evidence of cybercrimes within compromised systems.These cybercrimes are often perpetrated through the deployment of malware,which inevitably leaves discernible traces within the compromised systems.Forensic analysts are tasked with extracting and subsequently analyzing data,termed as artifacts,from these systems to gather evidence.Therefore,forensic analysts must sift through extensive datasets to isolate pertinent evidence.However,manually identifying suspicious traces among numerous artifacts is time-consuming and labor-intensive.Previous studies addressed such inefficiencies by integrating artificial intelligence(AI)technologies into digital forensics.Despite the efforts in previous studies,artifacts were analyzed without considering the nature of the data within them and failed to prove their efficiency through specific evaluations.In this study,we propose a system to prioritize suspicious artifacts from compromised systems infected with malware to facilitate efficient digital forensics.Our system introduces a double-checking method that recognizes the nature of data within target artifacts and employs algorithms ideal for anomaly detection.The key ideas of this method are:(1)prioritize suspicious artifacts and filter remaining artifacts using autoencoder and(2)further prioritize suspicious artifacts and filter remaining artifacts using logarithmic entropy.Our evaluation demonstrates that our system can identify malicious artifacts with high accuracy and that its double-checking method is more efficient than alternative approaches.Our system can significantly reduce the time required for forensic analysis and serve as a reference for future studies. 展开更多
关键词 Digital forensics autoencoder logarithmic entropy prioritization anomaly detection windows artifacts artificial intelligence
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Fuzzy-based risk prioritization for a hydrogen refueling facility in Malaysia 认领 引用 被引量：2
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作者 Hue-yee CHONG Mahidzal DAHARI +1 位作者 Hwa-jen YAP Ying-tai LOONG 《Journal of Zhejiang University-SCIENCE A》 SCIE EI CAS CSCD 2013年第8期565-573,共9页
Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Befor... Hydrogen is starting to be mentioned as an alternative fuel to replace the fossil fuel in future transportation applications due to its characteristics of zero greenhouse gas emission and high energy efficiency. Before hydrogen fuel and its facilities can be introduced to the public, relevant safety issues and its hazards must be assessed in order to avoid any chance of injury or loss. While a traditional risk assessment has difficulty in prioritizing the risk of failure modes, this paper proposes a new fuzzy-based risk evaluation technique which uses fuzzy value to prioritize the risk of various scenarios. In this study, the final risk of each failure modes was prioritized by using the MATLAB fuzzy logic tool box with a combination of two assessments. The first assessment was concerned with the criteria which affected the actual probability of occurrence. This assessment considered the availability of the standard that was applied to prevent the likelihood of the scenario occurring. On the other hand, the second assessment was focused on evaluating the consequence of the failure by taking into account the availability of detection and the complexity of the failure rather than only the severity of the scenarios. A total of 87 failure scenarios were identified using failure modes and effect analysis (FMEA) procedures on hydrogen refueling station models. Fuzzy-based assessments were performed through risk prioritizing various failure scenarios with a fuzzy value (0 to 1) and risk level (low, medium, and high) while a traditional risk assessment approach presented the risks only in forms of level (low, medium, and/or high). Availability of the fuzzy value enabled further prioritizing on the risk results that fell in the same level of risk. This study concluded that fuzzy-based risk evaluation is able to further prioritize the decisions when compared with a traditional risk assessment method. 展开更多
关键词 Risk criteria Risk prioritization Hydrogen refueling facility Fuzzy logic
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Prioritization of Sub-Watersheds in a Large Semi-Arid Drainage Basin (Southern Jordan) Using Morphometric Analysis, GIS, and Multivariate Statistics 认领 引用 被引量：2
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作者 Yahya Farhan Ali Anbar +3 位作者 Nisreen Al-Shaikh Haifa Almohammad Sireen Alshawamreh Manal Barghouthi 《Agricultural Sciences》 2018年第4期437-468,共32页
GIS-based morphometric analysis was employed to prioritize the W. Mujib-Wala watershed southern Jordan. Seventy six fourth-order sub-watersheds were prioritized using morphometric analysis of ten linear and shape para... GIS-based morphometric analysis was employed to prioritize the W. Mujib-Wala watershed southern Jordan. Seventy six fourth-order sub-watersheds were prioritized using morphometric analysis of ten linear and shape parameters. Each sub-watershed is prioritized by designated ranks based on the calculated compound parameter (Cp). The total score for each sub-basin is assigned as per erosion threat. The 76 sub-basins were grouped into four categories of priority: very high (12 sub-basins, 15.8% of the total), high (32 sub-watersheds, 42.1% of the total), moderate (25 sub-watersheds, 32.9% of the total), and low (7 sub-watersheds, 9.2% of the total). Sub-watersheds categorized as very high and high are subjected to high erosion risk, thus creating an urgent need for applying soil and water conservation measures. The relative diversity in land use practices and land cover, including variation in slope and soil types, are considered in proposing suitable conservation structures for sub-watersheds connected to each priority class. The adaptation of soil conservation measures priority-wise will reduce the erosivity effect on soil loss;while increasing infiltration rates;and water availability in soil profile. Principal component analysis (PCA) reduces the basic parameters and erosion risk parameters to three components, explaining 88% of the variance. The relationships of these components to the basic and erosion risk parameters were evaluated, and then the degree of inter-correlation among the morphometric parameters was explored. The verification of priority classes obtained through morphometric analysis was tested using Discriminant Analysis (DA). The results show a complete separation existing between the identified priority classes. Thus, soil erosion risk and geomorphic conditions are found entirely different from one class to another. The present results are intended to help decision makers to plan for efficient soil and water conservation measures to achieve future agricultural sustainability in the rainfed highlands of Jordan. 展开更多
关键词 Prioritization Morphometric Analysis GIS Discriminant Analysis Principal Component Analysis
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Prioritization of Promising Wadi Wala Watershed (Southern Jordan) Using GIS-Based Morphometric Analysis and Multivariate Statistics 认领 引用 被引量：1
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作者 Yahya Farhan Ali Anbar +2 位作者 Dalal Zreqat Haifa Almohammad Sireen Alshawamreh 《Open Journal of Geology》 CAS 2018年第2期135-160,共26页
GIS-based morphometric analysis was employed for prioritization of the Wadi Wala catchment, southern Jordan. Twenty three fourth-order sub-basins were prioritized based on morphometric analysis, then appropriate soil ... GIS-based morphometric analysis was employed for prioritization of the Wadi Wala catchment, southern Jordan. Twenty three fourth-order sub-basins were prioritized based on morphometric analysis, then appropriate soil and water conservation measures were proposed. Digital Elevation Model (DEM) and Arc GIS were used to delineate watersheds and to extract the drainage networks, and other required thematic maps (elevation and slope). LANDSAT data was used to prepare land use/land cover map, and a soil map was digitized using Arc GIS software. Linear and shape parameters were computed to prioritize 23 sub-watersheds, and ranks were designated based on the calculated compound parameter (Cp). Sub-basins grouped under a high priority class are exposed to high erosion risk;thus, they are of high potential for applying soil and water conservation measures. The current study substantiates the capability of morphometric analysis method, and geospatial technology in watershed prioritization. The Discriminant Analysis (DA) employed validates the priority classes (high, moderate, and low priority) achieved based on morphometric analysis, where they found statistically distinct from each other. Thus, it can be concluded that prioritization based only on morphometric analysis method is consistent, reliable, and of high capacity using GIS platform. Priority map along with soil, land user/cover, and slope information will help decision makers to execute proper soil and water conservation programs in the rainfed highlands of Jordan. 展开更多
关键词 Morphometric Analysis Prioritization Soil Erosion Loss Discriminant Analysis GIS Jordan
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Prioritization of W. Mujib Catchment (South Jordan) through Morphometric and Discriminant Analysis, GIS, and RS Techniques 认领 引用 被引量：1
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作者 Yahya Farhan Dalal Zreqat +2 位作者 Ali Anbar Haifa Almohammad Sireen Alshawamreh 《Journal of Geoscience and Environment Protection》 2018年第4期141-171,共31页
GIS and remote sensing were utilized for prioritizing the W. Mujib catchment. Fifty three fourth-order sub-watersheds were prioritized based on morphometric analysis of linear and shape parameters. ASTER DEM (v.2), to... GIS and remote sensing were utilized for prioritizing the W. Mujib catchment. Fifty three fourth-order sub-watersheds were prioritized based on morphometric analysis of linear and shape parameters. ASTER DEM (v.2), topographical maps, and Arc GIS (10.1) software, have been employed to delineate the 53 sub-basins, to extract the drainage networks, and to compute the required basic, linear, and shape parameters, and to compile the necessary thematic maps such as elevation and slope categories. The land use/land cover map was generated using ERDAS Imagine (2015), LANDSAT 8 image, and supervised classification (Maximum Likelihood Method). Soil map was digitized using the Arc GIS tool. Each sub-basin is prioritized by assigning ranks based on the calculated compound parameter (Cp). The final score for each sub-basin is ascribed as per erosion threat. The 53 sub-watersheds were grouped into four categories of priority: very high (15 sub-basins, 28.3% of the total), high (17 sub-basins, 32% of the total), moderate (16 sub-basins, 30.2% of the total), and low (5 sub-basins, 9.5% of the total). Sub-basins categorized as very high and high priority (60.3% of the total) are subjected to high erosion risk, thus, creating an urgent need for applying soil and water conservation measures. The validity of the prioritized four groups was tested statistically by means of Discriminant Analysis (DA), and a significant difference was found between the four priority classes. A relatively complete separation exists between the recognized priority classes;thus, they are statistically valid, distinct, and different from each other. The present results intend to help decision makers pay sufficient attention to soil and water conservation programs, and to encourage tree plantation over the government-owned sloping land. Such procedures are essential in order to minimize soil erosion loss, and to increase soil moisture on farms, thus, reducing the impact of recurrent droughts and the possibility of flooding downstream. 展开更多
关键词 Morphometric Analysis Prioritization Discriminant Analysis GIS Soil Conservation W. Mujib
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Fault Coverage-Based Test Case Prioritization and Selection Using African Buffalo Optimization 认领 引用
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作者 Shweta Singhal Nishtha Jatana +3 位作者 Ahmad F Subahi Charu Gupta Osamah Ibrahim Khalaf Youseef Alotaibi 《Computers, Materials & Continua》 SCIE EI 2023年第3期6755-6774,共20页
Software needs modifications and requires revisions regularly.Owing to these revisions,retesting software becomes essential to ensure that the enhancements made,have not affected its bug-free functioning.The time and ... Software needs modifications and requires revisions regularly.Owing to these revisions,retesting software becomes essential to ensure that the enhancements made,have not affected its bug-free functioning.The time and cost incurred in this process,need to be reduced by the method of test case selection and prioritization.It is observed that many nature-inspired techniques are applied in this area.African Buffalo Optimization is one such approach,applied to regression test selection and prioritization.In this paper,the proposed work explains and proves the applicability of the African Buffalo Optimization approach to test case selection and prioritization.The proposed algorithm converges in polynomial time(O(n2)).In this paper,the empirical evaluation of applying African Buffalo Optimization for test case prioritization is done on sample data set with multiple iterations.An astounding 62.5%drop in size and a 48.57%drop in the runtime of the original test suite were recorded.The obtained results are compared with Ant Colony Optimization.The comparative analysis indicates that African Buffalo Optimization and Ant Colony Optimization exhibit similar fault detection capabilities(80%),and a reduction in the overall execution time and size of the resultant test suite.The results and analysis,hence,advocate and encourages the use of African Buffalo Optimization in the area of test case selection and prioritization. 展开更多
关键词 Test case prioritization regression testing test case selection African buffalo optimization nature-inspired meta-heuristic
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