基于残差的混合软件可靠性预测模型

Gul Jabeen, Xi Yang, Luo Ping, Sabit Rahim, Gul Sahar, A. A. Shah
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引用次数: 3

摘要

软件可靠性是软件质量保证的关键特征之一。它主要与软件的缺陷联系在一起,这表明了软件开发中的一个主要因素。软件已经成为一个组织不可缺少的投资。用户更关心准确、高效的故障预测模型。早期故障预测模型可以降低测试成本,提高可靠性,提高软件质量。每种模型都需要精确的预测,但没有一种模型被证明能够有效、准确地建立软件可靠性模型。本文将两种最流行的可靠性预测模型结合起来,采用基于残差的马尔可夫方法得到最准确的可靠性预测结果。在美国海军战术数据系统上进行了实验分析和对比,验证了混合方法的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid software reliability prediction model based on residual errors
Software reliability is one of the key features of software quality assurance. It is primarily associated with the defects of software, which indicates a major factor in software development. Software has become an indispensable investment for an organization. The users are more concerned about accurate and efficient failure prediction model. Early fault prediction model can reduce the cost of the test, increase reliability and improve the quality of software. Precise prediction is desired from the every model but no model has proved to be successful at efficiently and accurately developing software reliability model. In this paper, the authors have combined two most popular reliability prediction models and get the most accurate output from them by using Markov method based on their residual errors. Furthermore, experiment analysis and comparison carried out on U.S. Navy Tactical Data System, which shows the accuracy of the hybrid approach.
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