In order to choose a set of reasonable CNC turning process parameters, a multi-step and multi process combination optimization method was proposed, in which both rough / finish machining, multiple pass in rough machin...
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Dependency updates often cause compilation errors when new dependency versions introduce changes that are incompatible with existing client code. Fixing breaking dependency updates is notoriously hard, as their root c...
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Generative artificial intelligence (AI) is revolutionizing many aspects of both academia and society. Its effective integration in computer science education is a current challenge for educators. This work presents an...
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A microlearning system providing up-to-date and on-time information relevant to the current work of the (bio)medical professionals was developed. The system uses a microlearning approach and adapts to the working proc...
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We provide support for polymorphism in static typestate analysis for object-oriented languages with upcasts and downcasts. Recent work has shown how typestate analysis can be embedded in the development of java progra...
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This paper proposes a three-factor nonlinear regression model for java-software size estimation. java is one of the most widely used programminglanguages in the world and is actively used in the development of variou...
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This paper proposes a three-factor nonlinear regression model for java-software size estimation. java is one of the most widely used programminglanguages in the world and is actively used in the development of various software projects. The software size estimation plays a key planning role at the early stages of software project planning for the successful implementation of software development projects. The software size estimation is valuable information that is used to predict software development effort estimation using parametric models such as COCOMO, COCOMO II, COSYSMO, etc. The aim of the study is to build the three-factor nonlinear regression model for early KLOC size estimation of java-software on the basis of multivariate Johnson SB family normalizing transformations to increase the reliability and accuracy of the software size estimation at the early stage of software project planning using UML class diagram metrics. The object of the study is the process of size estimation for open-source java-software. The subject of the study is the nonlinear regression models to estimate the software size. To achieve this goal we collected software code metrics information from 571 open-source java software projects. The obtained dataset is split up in training and testing samples accordingly Cross-Validation technique. The regression model building is based on an iterative method that includes bjective multivariate normalizing transformation, multivariable outliers detection, confidence and prediction interval building. The obtained nonlinear regression model is compared to the existing models by the regression models quality criteria such as the determination coefficient, mean magnitude of relative error (MMRE) and the percentage of prediction of the relative error level 0.25 (PRED(0.25)). The comparison results confirm increasing the accuracy of the software size estimation using the obtained regression model on both training and testing samples. The prospects f
The article presents the mechanisms of safe programming in java applications. We indicate some mechanisms of protection against known vulnerabilities of java applications considering concurrent programs, finalizers, a...
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This paper proposes a remote vocational education assistance system based on javalanguage and Socket language. The purpose is to improve the effect of online broadcasting, reduce the delay of sound and image transmis...
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Worked code examples are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the examp...
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Concolic and many Concolic-based testing methods play an important role in saving the manual testing effort by fully automate the unit testing process. However, the performance of those methods is a big challenge when...
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