A three-step XML Schema modeling method is presented, namely first establishing a diagram of conceptual modeling, then transforming it to UML class diagram and finally mapping it to XML Schema. A case study of handlin...A three-step XML Schema modeling method is presented, namely first establishing a diagram of conceptual modeling, then transforming it to UML class diagram and finally mapping it to XML Schema. A case study of handling furniture design data is given to illustrate the detail of conversion process.展开更多
Software system can be classified into many function modules from the perspective of user. Unified modeling language( UML) class diagram of each function module was extracted,and design characteristic metrics which in...Software system can be classified into many function modules from the perspective of user. Unified modeling language( UML) class diagram of each function module was extracted,and design characteristic metrics which influenced software maintainability were selected based on UML class diagram.Choosing metrics of UML class diagram as predictors,and mean maintenance time of function module was regarded as software maintainability parameter. Software maintainability models were built by using back propagation( BP) neural network and radial basis function( RBF) neural network, respectively and were simulated by MATLAB. In order to evaluate the performance of models,the training results were analyzed and compared with leaveone-out cross-validation and model performance evaluation criterion. The result indicated that RBF arithmetic was superior to BP arithmetic in predicting software maintainability.展开更多
基金Supported by the National Key Project Foundation of China (No. 2001BA201A06)
文摘A three-step XML Schema modeling method is presented, namely first establishing a diagram of conceptual modeling, then transforming it to UML class diagram and finally mapping it to XML Schema. A case study of handling furniture design data is given to illustrate the detail of conversion process.
文摘Software system can be classified into many function modules from the perspective of user. Unified modeling language( UML) class diagram of each function module was extracted,and design characteristic metrics which influenced software maintainability were selected based on UML class diagram.Choosing metrics of UML class diagram as predictors,and mean maintenance time of function module was regarded as software maintainability parameter. Software maintainability models were built by using back propagation( BP) neural network and radial basis function( RBF) neural network, respectively and were simulated by MATLAB. In order to evaluate the performance of models,the training results were analyzed and compared with leaveone-out cross-validation and model performance evaluation criterion. The result indicated that RBF arithmetic was superior to BP arithmetic in predicting software maintainability.
