| An Approach to Early Prediction of Software Quality |
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| 作者姓名： | YAO Lan YANG Bo |
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| 作者单位： | [1]School of Electronic Engineering, University of Electronic Science and Technology of China Chengdu 610054 China [2]School of Mechatronics Engineering, University of Electronic Science and Technology of China Chengdu 610054 China |
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| 基金项目： | Supported by the National Defense Pro-research Project |
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| 摘 要： | Due to the rapid development of computers and their applications,early software quality prediction in software industry becomes more and more crucial. Software quality prediction model is very helpful for decision-makings such as the allocation of resource in module verification and validation. Nevertheless,due to the complicated situations of software development process in the early stage,the applicability and accuracy of these models are still under research. In this paper,a software quality prediction model based on a fuzzy neural network is presented,which takes into account both the internal factors and external factors of software. With hybrid-learning algorithm,the proposed model can deal with multiple forms of data as well as incomplete information,which helps identify design errors early and avoid expensive rework.
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| 关 键 词： | 软件质量 早期预测 模糊神经网络 预测模型 软件内部属性 |
| 收稿时间： | 2006-05-29 |
An Approach to Early Prediction of Software Quality |
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| YAO Lan YANG Bo.An Approach to Early Prediction of Software Quality[J].Journal of Electronic Science Technology of China,2007,5(1):23-28. |
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| Authors: | YAO Lan YANG Bo |
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| Abstract: | Due to the rapid development of computers and their applications, early software quality prediction in software industry becomes more and more cruciaL Software quality prediction model is very helpful for decision-makings such as the allocation of resource in module verification and validation. Nevertheless, due to the complicated situations of software development process in the early stage, the applicability and accuracy of these models are still under research. In this paper, a software quality prediction model based on a fuzzy neural network is presented, which takes into account both the internal factors and external factors of software. With hybrid-learning algorithm, the proposed model can deal with multiple forms of data as well as incomplete information, which helps identify design errors early and avoid expensive rework. |
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| Keywords: | early quality prediction fuzzy neural network prediction model software internal attributes software quality attributes |
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