Standard costing is used as a control for product costing. But with life cycle becoming shorter, costing should be done at the design and development stage of a product. This is achieved through target costing.The imp...Standard costing is used as a control for product costing. But with life cycle becoming shorter, costing should be done at the design and development stage of a product. This is achieved through target costing.The implementation of target costing and target pricing is done with the ultimate purpose of cost reduction, cost understanding, continuous improvement, competitiveness, early purchasing and supplier involvement, and improved design and accountability by manufacturers. The study explores the participation of the purchasing and supply chain management＇s role in target costing and target pricing process. Supply management plays an active role in monitoring the ongoing cost and performance of suppliers during the early stages of product development. Implementation of target costing and target pricing in various organizations are also explored. Leading Japanese manufacturers have used target costing and target pricing systems to their advantage and the paper also examines the adaptation of the Western companies to these proactive cost management techniques to improve their product development processes.展开更多
System analysts often use software fault prediction models to identify fault-prone modules during the design phase of the software development life cycle. The models help predict faulty modules based on the software m...System analysts often use software fault prediction models to identify fault-prone modules during the design phase of the software development life cycle. The models help predict faulty modules based on the software metrics that are input to the models. In this study, we consider 20 types of metrics to develop a model using an extreme learning machine associated with various kernel methods. We evaluate the effectiveness of the mode using a proposed framework based on the cost and efficiency in the testing phases. The evaluation process is carried out by considering case studies for 30 object-oriented software systems. Experimental results demonstrate that the application of a fault prediction model is suitable for projects with the percentage of faulty classes below a certain threshold, which depends on the efficiency of fault identification(low: 47.28%; median: 39.24%; high: 25.72%). We consider nine feature selection techniques to remove the irrelevant metrics and to select the best set of source code metrics for fault prediction.展开更多
文摘Standard costing is used as a control for product costing. But with life cycle becoming shorter, costing should be done at the design and development stage of a product. This is achieved through target costing.The implementation of target costing and target pricing is done with the ultimate purpose of cost reduction, cost understanding, continuous improvement, competitiveness, early purchasing and supplier involvement, and improved design and accountability by manufacturers. The study explores the participation of the purchasing and supply chain management＇s role in target costing and target pricing process. Supply management plays an active role in monitoring the ongoing cost and performance of suppliers during the early stages of product development. Implementation of target costing and target pricing in various organizations are also explored. Leading Japanese manufacturers have used target costing and target pricing systems to their advantage and the paper also examines the adaptation of the Western companies to these proactive cost management techniques to improve their product development processes.
基金the FIST project,of DST, government of India for sponsoring the work on web engineering and cloud based computing
文摘System analysts often use software fault prediction models to identify fault-prone modules during the design phase of the software development life cycle. The models help predict faulty modules based on the software metrics that are input to the models. In this study, we consider 20 types of metrics to develop a model using an extreme learning machine associated with various kernel methods. We evaluate the effectiveness of the mode using a proposed framework based on the cost and efficiency in the testing phases. The evaluation process is carried out by considering case studies for 30 object-oriented software systems. Experimental results demonstrate that the application of a fault prediction model is suitable for projects with the percentage of faulty classes below a certain threshold, which depends on the efficiency of fault identification(low: 47.28%; median: 39.24%; high: 25.72%). We consider nine feature selection techniques to remove the irrelevant metrics and to select the best set of source code metrics for fault prediction.
