Software development process basically consists of phases, planned and executed in series: 1) feasibility study;2) requirements;3) design and 4) implementation, prior to production and maintenance. At the end of each ...Software development process basically consists of phases, planned and executed in series: 1) feasibility study;2) requirements;3) design and 4) implementation, prior to production and maintenance. At the end of each phase, there may be an official management decision (go/not go) depending upon cost, time or other reasons. Within each phase or across-phases, parallelism or concurrency can be achieved if modularity and/or independence of functionality exist(s). We propose a different approach to software development process that allows an improved parallel planning and execution of development effort beyond modularity and functionality independence. The goal is to shorten development time while possibly cutting cost and maintaining the same intended quality of performance. An example development is sketched.展开更多
Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely h...Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.展开更多
Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Method...Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.展开更多
Scientific modeling provides mathematical abstractions of real-world systems and builds software as implementations of these mathematical abstractions.Ocean science is a multidisciplinary discipline developing scienti...Scientific modeling provides mathematical abstractions of real-world systems and builds software as implementations of these mathematical abstractions.Ocean science is a multidisciplinary discipline developing scientific models and simulations as ocean sys-tem models that are an essential research asset.In software engineering and information systems research,modeling is also an essential activity.In particular,business process modeling for business process management and systems engineering is the activity of representing processes of an enterprise,so that the current process may be analyzed,improved and automated.In this paper,we employ process modeling for analyzing sci-entific software development in ocean science to advance the state in engineering of ocean system models and to better understand how ocean system models are developed and maintained in ocean science.We interviewed domain experts in semi-structured inter-views,analyzed the results via thematic analysis,and modeled the results via the Busi-ness Process Modeling Notation(BPMN).The processes modeled as a result describe an aspired state of software development in the domain,which are often not(yet)imple-mented.This enables existing processes in simulation-based system engineering to be improved with the help of these process models.展开更多
Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace id...Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace identification,peak-picking,and frequency domain decomposition method in modal analysis based on ambient excitation,and the effectiveness of these three methods is verified through finite element calculation and numerical simulation,Then the damage element is added to the finite element model to simulate the crack,and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location.Finally,the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform.The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape,both damage identification methods can accurately identify and locate the damage,and the developed software platform is simple and efficient.展开更多
Recently software industry has paid significant attention to customizing software products across distributed boundaries.Communicating the requirements of multiple clients across distributed borders is a crucial chall...Recently software industry has paid significant attention to customizing software products across distributed boundaries.Communicating the requirements of multiple clients across distributed borders is a crucial challenge for the software customization process.Local decision-making and local development at the client site are considered methods for reducing difficulties in communicating the requirements of multiple clients across distributed boundaries.This paper introduces a new model called the onshore development model(ODM)for accomplishing the customization requests in the distributed development process of software.This model presents a scenario for enhancing the onsite development of specific requirements to reduce delays andmisunderstandings between the clients and the team involved.This model depends on moving the development process to the client’s location.Three empirical studies were conducted to evaluate the proposed model to measure its productivity,time performance,and cost reduction.The proposed model has been compared with two other models:the basic model(BM),which allocates the decision-making process and the development process for teams at the vendor’s location,and the local decision-making model(LDec),which assigns the decision-making process for team at the client’s location.The results of the empirical studies showed significant outperforming of the proposed model over the basic model and local decision-making model in productivity,time performance,and cost reduction.The productivity of the proposed model improved by 39%and 10%more than the basic model and the local decision-making model,respectively.In addition,the time performance of the proposed model became faster by 49%and 20.8%than the basic model and the local decision-making model,respectively.Also,it reduced the total cost of the development process by 31%in terms of the salaries of all persons involved in requirements collecting,decision-making,and development.展开更多
This research recognizes the limitation and challenges of adaptingand applying Process Mining as a powerful tool and technique in theHypothetical Software Architecture (SA) Evaluation Framework with thefeatures and fa...This research recognizes the limitation and challenges of adaptingand applying Process Mining as a powerful tool and technique in theHypothetical Software Architecture (SA) Evaluation Framework with thefeatures and factors of lightweightness. Process mining deals with the largescalecomplexity of security and performance analysis, which are the goalsof SA evaluation frameworks. As a result of these conjectures, all ProcessMining researches in the realm of SA are thoroughly reviewed, and ninechallenges for Process Mining Adaption are recognized. Process mining isembedded in the framework and to boost the quality of the SA model forfurther analysis, the framework nominates architectural discovery algorithmsFlower, Alpha, Integer Linear Programming (ILP), Heuristic, and Inductiveand compares them vs. twelve quality criteria. Finally, the framework’s testingon three case studies approves the feasibility of applying process mining toarchitectural evaluation. The extraction of the SA model is also done by thebest model discovery algorithm, which is selected by intensive benchmarkingin this research. This research presents case studies of SA in service-oriented,Pipe and Filter, and component-based styles, modeled and simulated byHierarchical Colored Petri Net techniques based on the cases’ documentation.Processminingwithin this framework dealswith the system’s log files obtainedfrom SA simulation. Applying process mining is challenging, especially for aSA evaluation framework, as it has not been done yet. The research recognizesthe problems of process mining adaption to a hypothetical lightweightSA evaluation framework and addresses these problems during the solutiondevelopment.展开更多
In the textile industry,garment manufacturing contains four major pro-cesses containing cutting,sewing,finishing,and packaging.Sewing is the most crucial and intricate section,dealing with a large number of varied oper...In the textile industry,garment manufacturing contains four major pro-cesses containing cutting,sewing,finishing,and packaging.Sewing is the most crucial and intricate section,dealing with a large number of varied operations.A successful sewing process needs to be optimized regarding different factors,including time,sewing equipment,and skilled workers.Assembly lineflow is combined by a set of operations with a particular sequence.The utmost impor-tance of all garment industry is to arrange the workstations to minimize the num-ber of employees in order to produce at the best productive rate with the most reasonable cost,shortest time,and satisfying quality.In most garment factories,the production lines are balanced using the empirical judgment of the line man-agers.For the whole process the data of production time at each step,labor pro-ductivity,proper choices of equipment were always needed to calculate line efficiency.As far as the issue is concerned,there has not been an academically sewing process analyzing software providing adequate data of sewing motions and sewing time as the credible input for the line balancing tasks.Towards this goal,this paper presents the results of research on optimizing academically self-built software to analyze the sewing process of knitted products applied to industrial production using Java programming language on Google tools.The results achieved by the software are not only to analyze sewing products and the technological sewing process,calculate the sewing time on the machine but also analyze the sewing activities of workers into manipulations,movements,and motions to calculate the preparation time for two typical knitted products,namely,Polo-Shirt and T-Shirt with the case studies at General Textile Garment Joint Stock Company Hanoi and Star Fashion Company Limited.展开更多
Software engineering is a highly practical major,and students need a lot of hands-on practice to transform the theoretical contents learned in class into the practical ability to solve practical problems,so practical ...Software engineering is a highly practical major,and students need a lot of hands-on practice to transform the theoretical contents learned in class into the practical ability to solve practical problems,so practical courses are an essential and important part in the process of training talents in software engineering.From the point of view of cultivating talents in software engineering,this paper expounds the important position of practical courses in software engineering in the process of cultivating talents,analyzes the problems in the existing practical courses,and puts forward the construction ideas and characteristics of practical courses in software engineering which strengthen the foundation,advance steadily,and face the output.Taking the practical course for software system development as an example,this paper introduces in detail the concrete implementation process,achievements,existing problems and countermeasures of the course.展开更多
In project-based organizations knowledge is a critical resource used to develop and deliver products and services with a high level of quality. Therefore, a systematic and sustainable process is necessary to coordinat...In project-based organizations knowledge is a critical resource used to develop and deliver products and services with a high level of quality. Therefore, a systematic and sustainable process is necessary to coordinate knowledge management, project management and product lifecycle. This scenario predominates in companies focused on the creation and maintenance of information systems. This article presents an exploratory study based on a framework that integrates cognitive, managerial, and operational processes in a public Brazilian organization that provides services in the area of information and communications technology, focusing on the construction and maintenance of information systems. Those processes are operationalized by three management models considering knowledge, project, and software development processes. Our proposal aims to understand the relationships between those three management models and their influence on the software development process in the organization under study. Our premise is based on the principle that cognitive management, project management, and software development management must be integrated to fulfill the demands of product development and service provision. The research data was composed of registers of working hours spent on software development and maintenance projects involving 244 people allocated to 5064 projects in the period from 2007 to 2013. The study resulted in the identification of the relationships among the three management models adopted by the organization, with emphasis on knowledge management activities, which were not directly identified, making it difficult to account for and measure them. We established a set of activities connected to each one of the knowledge management model phases. Since those activities were not visible before, our approach contributed to build a systematic process to register and relate activities linked to the dimensions of cognitive processes, project management, and software construction.展开更多
Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learn...Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.展开更多
This paper presents a methodology driven by database constraints for designing and developing(database)software applications.Much needed and with excellent results,this paradigm guarantees the highest possible quality...This paper presents a methodology driven by database constraints for designing and developing(database)software applications.Much needed and with excellent results,this paradigm guarantees the highest possible quality of the managed data.The proposed methodology is illustrated with an easy to understand,yet complex medium-sized genealogy software application driven by more than 200 database constraints,which fully meets such expectations.展开更多
Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineeri...Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.展开更多
This paper is giving an overview of the process of requirement analysis for software development. Here I have discussed about key parts in requirement analysing, gathering relevant materials, functional analysis and a...This paper is giving an overview of the process of requirement analysis for software development. Here I have discussed about key parts in requirement analysing, gathering relevant materials, functional analysis and allocations, how to improve and make a quality process and also document development as well and many more which relates to requirement analysis process. The scope of this study is not a generalized approach but rather discuss through specific cases such as like Dutch flower case. It describes the main areas of requirement process in practice, and highlights. I hope that readers will find this paper useful in guiding them toward the knowledge and resources they needed.展开更多
There are several software process models that have been proposed and are based on task involved in developing and maintaining software product. The large number of software projects not meeting their expectation in t...There are several software process models that have been proposed and are based on task involved in developing and maintaining software product. The large number of software projects not meeting their expectation in terms of functionality, cost, delivery schedule and effective project management appears to be lacking. In this paper, we present a new software fusion process model, which depicts the essential phases of a software project from initiate stage until the product is retired. Fusion is component based software process model, where each component implements a problem solving model. This approach reduces the risk associated with cost and time, as these risks will be limited to a component only and ensure the overall quality of software system by considering the changing requirements of customer, risk assessment, identification, evaluation and composition of relative concerns at each phase of development process.展开更多
Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detecti...Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.展开更多
The development of women’s higher education in China can be divided into four stages:emergence(1908-1948);foundation(1949-1976);accelerating development(1977-2008);and the qualitative leap(2009-2020).This work consid...The development of women’s higher education in China can be divided into four stages:emergence(1908-1948);foundation(1949-1976);accelerating development(1977-2008);and the qualitative leap(2009-2020).This work considers the principal institutional mechanisms that contributed to this development.First,flexibly planned parenthood gradually promoted gender equality and openness in society facilitated by systematic“awards,grants,and loans”initiatives to support women’s higher education economically.Second,compulsory education ensured that left-out and migrant children had access to higher education.Third,effective connectivity across different education types bridged education gaps between those with different levels of education.Fourth,China made great efforts to invite and integrate international experiences that promoted the development of women’s higher education.Looking beyond these achievements,we also discuss the future trends of women’s higher education in China.展开更多
文摘Software development process basically consists of phases, planned and executed in series: 1) feasibility study;2) requirements;3) design and 4) implementation, prior to production and maintenance. At the end of each phase, there may be an official management decision (go/not go) depending upon cost, time or other reasons. Within each phase or across-phases, parallelism or concurrency can be achieved if modularity and/or independence of functionality exist(s). We propose a different approach to software development process that allows an improved parallel planning and execution of development effort beyond modularity and functionality independence. The goal is to shorten development time while possibly cutting cost and maintaining the same intended quality of performance. An example development is sketched.
文摘Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.
文摘Objective To identify the critical risks in the process of innovative drug research and development,and to provide reference for improving the efficiency of innovative drug development and risk control in China.Methods Expert investigation and analytic hierarchy process were used to determine the weights of different risks.Results and Conclusion The research and analysis results showed that the risks at different stages of development had different effects on the success rate of drug development,among which the risk at the drug discovery stage influenced the most.In the drug discovery stage,inappropriate target selection had the greatest impact on the success rate of drug development.The lack of appropriate cell tissue or animal models had the greatest impact on the success rate of drug development from the discovery of a compound to the application for clinical trials.The difference in changes between nonclinical and clinical studies had the greatest impact on the success rate of drug development from early clinical studies to pivotal clinical studies.Incorrect dose selection had the greatest impact on the success rate of drug development from pivotal clinical studies to marketing authorization applications.The biggest impact from the marketing authorization application to the approval stage was inadequate communication with regulators.After investigating the weight of risk factors in the process of innovative drug development based on scientific methods,a new perspective for the risk control of new drug development and improving the research and development efficiency is provided.
基金This work was funded by the Deutsche Forschungsgemeinschaft(DFG——German Research Foundation),grant no.HA 2038/8-1——425916241.
文摘Scientific modeling provides mathematical abstractions of real-world systems and builds software as implementations of these mathematical abstractions.Ocean science is a multidisciplinary discipline developing scientific models and simulations as ocean sys-tem models that are an essential research asset.In software engineering and information systems research,modeling is also an essential activity.In particular,business process modeling for business process management and systems engineering is the activity of representing processes of an enterprise,so that the current process may be analyzed,improved and automated.In this paper,we employ process modeling for analyzing sci-entific software development in ocean science to advance the state in engineering of ocean system models and to better understand how ocean system models are developed and maintained in ocean science.We interviewed domain experts in semi-structured inter-views,analyzed the results via thematic analysis,and modeled the results via the Busi-ness Process Modeling Notation(BPMN).The processes modeled as a result describe an aspired state of software development in the domain,which are often not(yet)imple-mented.This enables existing processes in simulation-based system engineering to be improved with the help of these process models.
文摘Modal and damage identification based on ambient excitation can greatly improve the efficiency of high-speed railway bridge vibration detection.This paper first describes the basic principles of stochastic subspace identification,peak-picking,and frequency domain decomposition method in modal analysis based on ambient excitation,and the effectiveness of these three methods is verified through finite element calculation and numerical simulation,Then the damage element is added to the finite element model to simulate the crack,and the curvature mode difference and the curvature mode area difference square ratio are calculated by using the stochastic subspace identification results to verify their ability of damage identification and location.Finally,the above modal and damage identification techniques are integrated to develop a bridge modal and damage identification software platform.The final results show that all three modal identification methods can accurately identify the vibration frequency and mode shape,both damage identification methods can accurately identify and locate the damage,and the developed software platform is simple and efficient.
文摘Recently software industry has paid significant attention to customizing software products across distributed boundaries.Communicating the requirements of multiple clients across distributed borders is a crucial challenge for the software customization process.Local decision-making and local development at the client site are considered methods for reducing difficulties in communicating the requirements of multiple clients across distributed boundaries.This paper introduces a new model called the onshore development model(ODM)for accomplishing the customization requests in the distributed development process of software.This model presents a scenario for enhancing the onsite development of specific requirements to reduce delays andmisunderstandings between the clients and the team involved.This model depends on moving the development process to the client’s location.Three empirical studies were conducted to evaluate the proposed model to measure its productivity,time performance,and cost reduction.The proposed model has been compared with two other models:the basic model(BM),which allocates the decision-making process and the development process for teams at the vendor’s location,and the local decision-making model(LDec),which assigns the decision-making process for team at the client’s location.The results of the empirical studies showed significant outperforming of the proposed model over the basic model and local decision-making model in productivity,time performance,and cost reduction.The productivity of the proposed model improved by 39%and 10%more than the basic model and the local decision-making model,respectively.In addition,the time performance of the proposed model became faster by 49%and 20.8%than the basic model and the local decision-making model,respectively.Also,it reduced the total cost of the development process by 31%in terms of the salaries of all persons involved in requirements collecting,decision-making,and development.
基金This paper is supported by Research Grant Number:PP-FTSM-2022.
文摘This research recognizes the limitation and challenges of adaptingand applying Process Mining as a powerful tool and technique in theHypothetical Software Architecture (SA) Evaluation Framework with thefeatures and factors of lightweightness. Process mining deals with the largescalecomplexity of security and performance analysis, which are the goalsof SA evaluation frameworks. As a result of these conjectures, all ProcessMining researches in the realm of SA are thoroughly reviewed, and ninechallenges for Process Mining Adaption are recognized. Process mining isembedded in the framework and to boost the quality of the SA model forfurther analysis, the framework nominates architectural discovery algorithmsFlower, Alpha, Integer Linear Programming (ILP), Heuristic, and Inductiveand compares them vs. twelve quality criteria. Finally, the framework’s testingon three case studies approves the feasibility of applying process mining toarchitectural evaluation. The extraction of the SA model is also done by thebest model discovery algorithm, which is selected by intensive benchmarkingin this research. This research presents case studies of SA in service-oriented,Pipe and Filter, and component-based styles, modeled and simulated byHierarchical Colored Petri Net techniques based on the cases’ documentation.Processminingwithin this framework dealswith the system’s log files obtainedfrom SA simulation. Applying process mining is challenging, especially for aSA evaluation framework, as it has not been done yet. The research recognizesthe problems of process mining adaption to a hypothetical lightweightSA evaluation framework and addresses these problems during the solutiondevelopment.
基金This study was carried out within the framework of the topic Science and Technology 01C–02/04–2019–3.
文摘In the textile industry,garment manufacturing contains four major pro-cesses containing cutting,sewing,finishing,and packaging.Sewing is the most crucial and intricate section,dealing with a large number of varied operations.A successful sewing process needs to be optimized regarding different factors,including time,sewing equipment,and skilled workers.Assembly lineflow is combined by a set of operations with a particular sequence.The utmost impor-tance of all garment industry is to arrange the workstations to minimize the num-ber of employees in order to produce at the best productive rate with the most reasonable cost,shortest time,and satisfying quality.In most garment factories,the production lines are balanced using the empirical judgment of the line man-agers.For the whole process the data of production time at each step,labor pro-ductivity,proper choices of equipment were always needed to calculate line efficiency.As far as the issue is concerned,there has not been an academically sewing process analyzing software providing adequate data of sewing motions and sewing time as the credible input for the line balancing tasks.Towards this goal,this paper presents the results of research on optimizing academically self-built software to analyze the sewing process of knitted products applied to industrial production using Java programming language on Google tools.The results achieved by the software are not only to analyze sewing products and the technological sewing process,calculate the sewing time on the machine but also analyze the sewing activities of workers into manipulations,movements,and motions to calculate the preparation time for two typical knitted products,namely,Polo-Shirt and T-Shirt with the case studies at General Textile Garment Joint Stock Company Hanoi and Star Fashion Company Limited.
文摘Software engineering is a highly practical major,and students need a lot of hands-on practice to transform the theoretical contents learned in class into the practical ability to solve practical problems,so practical courses are an essential and important part in the process of training talents in software engineering.From the point of view of cultivating talents in software engineering,this paper expounds the important position of practical courses in software engineering in the process of cultivating talents,analyzes the problems in the existing practical courses,and puts forward the construction ideas and characteristics of practical courses in software engineering which strengthen the foundation,advance steadily,and face the output.Taking the practical course for software system development as an example,this paper introduces in detail the concrete implementation process,achievements,existing problems and countermeasures of the course.
文摘In project-based organizations knowledge is a critical resource used to develop and deliver products and services with a high level of quality. Therefore, a systematic and sustainable process is necessary to coordinate knowledge management, project management and product lifecycle. This scenario predominates in companies focused on the creation and maintenance of information systems. This article presents an exploratory study based on a framework that integrates cognitive, managerial, and operational processes in a public Brazilian organization that provides services in the area of information and communications technology, focusing on the construction and maintenance of information systems. Those processes are operationalized by three management models considering knowledge, project, and software development processes. Our proposal aims to understand the relationships between those three management models and their influence on the software development process in the organization under study. Our premise is based on the principle that cognitive management, project management, and software development management must be integrated to fulfill the demands of product development and service provision. The research data was composed of registers of working hours spent on software development and maintenance projects involving 244 people allocated to 5064 projects in the period from 2007 to 2013. The study resulted in the identification of the relationships among the three management models adopted by the organization, with emphasis on knowledge management activities, which were not directly identified, making it difficult to account for and measure them. We established a set of activities connected to each one of the knowledge management model phases. Since those activities were not visible before, our approach contributed to build a systematic process to register and relate activities linked to the dimensions of cognitive processes, project management, and software construction.
基金This Research is funded by Researchers Supporting Project Number(RSPD2024R947),King Saud University,Riyadh,Saudi Arabia.
文摘Software project outcomes heavily depend on natural language requirements,often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements.Researchers are exploring machine learning to predict software bugs,but a more precise and general approach is needed.Accurate bug prediction is crucial for software evolution and user training,prompting an investigation into deep and ensemble learning methods.However,these studies are not generalized and efficient when extended to other datasets.Therefore,this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems.The methods involved feature selection,which is used to reduce the dimensionality and redundancy of features and select only the relevant ones;transfer learning is used to train and test the model on different datasets to analyze how much of the learning is passed to other datasets,and ensemble method is utilized to explore the increase in performance upon combining multiple classifiers in a model.Four National Aeronautics and Space Administration(NASA)and four Promise datasets are used in the study,showing an increase in the model’s performance by providing better Area Under the Receiver Operating Characteristic Curve(AUC-ROC)values when different classifiers were combined.It reveals that using an amalgam of techniques such as those used in this study,feature selection,transfer learning,and ensemble methods prove helpful in optimizing the software bug prediction models and providing high-performing,useful end mode.
文摘This paper presents a methodology driven by database constraints for designing and developing(database)software applications.Much needed and with excellent results,this paradigm guarantees the highest possible quality of the managed data.The proposed methodology is illustrated with an easy to understand,yet complex medium-sized genealogy software application driven by more than 200 database constraints,which fully meets such expectations.
文摘Mechatronic product development is a complex and multidisciplinary field that encompasses various domains, including, among others, mechanical engineering, electrical engineering, control theory and software engineering. The integration of artificial intelligence technologies is revolutionizing this domain, offering opportunities to enhance design processes, optimize performance, and leverage vast amounts of knowledge. However, human expertise remains essential in contextualizing information, considering trade-offs, and ensuring ethical and societal implications are taken into account. This paper therefore explores the existing literature regarding the application of artificial intelligence as a comprehensive database, decision support system, and modeling tool in mechatronic product development. It analyzes the benefits of artificial intelligence in enabling domain linking, replacing human expert knowledge, improving prediction quality, and enhancing intelligent control systems. For this purpose, a consideration of the V-cycle takes place, a standard in mechatronic product development. Along this, an initial assessment of the AI potential is shown and important categories of AI support are formed. This is followed by an examination of the literature with regard to these aspects. As a result, the integration of artificial intelligence in mechatronic product development opens new possibilities and transforms the way innovative mechatronic systems are conceived, designed, and deployed. However, the approaches are only taking place selectively, and a holistic view of the development processes and the potential for robust and context-sensitive artificial intelligence along them is still needed.
文摘This paper is giving an overview of the process of requirement analysis for software development. Here I have discussed about key parts in requirement analysing, gathering relevant materials, functional analysis and allocations, how to improve and make a quality process and also document development as well and many more which relates to requirement analysis process. The scope of this study is not a generalized approach but rather discuss through specific cases such as like Dutch flower case. It describes the main areas of requirement process in practice, and highlights. I hope that readers will find this paper useful in guiding them toward the knowledge and resources they needed.
文摘There are several software process models that have been proposed and are based on task involved in developing and maintaining software product. The large number of software projects not meeting their expectation in terms of functionality, cost, delivery schedule and effective project management appears to be lacking. In this paper, we present a new software fusion process model, which depicts the essential phases of a software project from initiate stage until the product is retired. Fusion is component based software process model, where each component implements a problem solving model. This approach reduces the risk associated with cost and time, as these risks will be limited to a component only and ensure the overall quality of software system by considering the changing requirements of customer, risk assessment, identification, evaluation and composition of relative concerns at each phase of development process.
文摘Structural development defects essentially refer to code structure that violates object-oriented design principles. They make program maintenance challenging and deteriorate software quality over time. Various detection approaches, ranging from traditional heuristic algorithms to machine learning methods, are used to identify these defects. Ensemble learning methods have strengthened the detection of these defects. However, existing approaches do not simultaneously exploit the capabilities of extracting relevant features from pre-trained models and the performance of neural networks for the classification task. Therefore, our goal has been to design a model that combines a pre-trained model to extract relevant features from code excerpts through transfer learning and a bagging method with a base estimator, a dense neural network, for defect classification. To achieve this, we composed multiple samples of the same size with replacements from the imbalanced dataset MLCQ1. For all the samples, we used the CodeT5-small variant to extract features and trained a bagging method with the neural network Roberta Classification Head to classify defects based on these features. We then compared this model to RandomForest, one of the ensemble methods that yields good results. Our experiments showed that the number of base estimators to use for bagging depends on the defect to be detected. Next, we observed that it was not necessary to use a data balancing technique with our model when the imbalance rate was 23%. Finally, for blob detection, RandomForest had a median MCC value of 0.36 compared to 0.12 for our method. However, our method was predominant in Long Method detection with a median MCC value of 0.53 compared to 0.42 for RandomForest. These results suggest that the performance of ensemble methods in detecting structural development defects is dependent on specific defects.
基金“Promoting research by writing”:Exploring the code of writing,supported by the Special Fund for basic scientific research of the Central University,Northwestern Polytechnical University(project no.KCJS23WT25).“Research on the construction of the linking-up curriculum system:Taking the industry characteristic research university as an example”was established by the Ministry of Education’s Youth Fund for Humanities and Social Sciences,the Department of Social Sciences of the Ministry of Education(project no.23YJC880099).
文摘The development of women’s higher education in China can be divided into four stages:emergence(1908-1948);foundation(1949-1976);accelerating development(1977-2008);and the qualitative leap(2009-2020).This work considers the principal institutional mechanisms that contributed to this development.First,flexibly planned parenthood gradually promoted gender equality and openness in society facilitated by systematic“awards,grants,and loans”initiatives to support women’s higher education economically.Second,compulsory education ensured that left-out and migrant children had access to higher education.Third,effective connectivity across different education types bridged education gaps between those with different levels of education.Fourth,China made great efforts to invite and integrate international experiences that promoted the development of women’s higher education.Looking beyond these achievements,we also discuss the future trends of women’s higher education in China.
