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Predicting Systems Performance through Requirements Quality Attributes Model

机译:通过要求质量属性模型预测系统性能

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Poor requirements definition can adversely impact system cost and performance for government acquisition programs. This can be mitigated by ensuring requirements statements are written in a clear and unambiguous manner that reflects high linguistic quality. This paper introduces a statistical model that uses requirements quality factors to predict system operational performance. This model is created using empirical data from current major acquisition programs within the federal government. Operational Requirements Documents and Operational Test Reports are the data sources, respectively, for the system requirements statements and the accompanying operational test results used for model development. A commercial-off-the-shelf requirements quality analysis tool is used to determine the linguistic quality metrics for the requirements statements. Following model construction, cross validation of the data is employed to confirm the predictive value of the model. In all, the results establish that requirements quality is indeed a predictive factor for end system operational performance; the resulting statistical model can inform requirements decisions based on likelihood of successful operational performance.
机译:不良需求定义可能对政府收购方案产生不利影响的系统成本和表现。这可以通过确保以明确和明确的方式编写的要求陈述来缓解,这反映了高语言质量。本文介绍了一种统计模型,它使用要求质量因素来预测系统操作性能。该模型是使用联邦政府内的当前主要收购计划的经验数据创建。操作要求文件和操作测试报告分别用于数据源,用于系统要求陈述和用于模型开发的随附的操作测试结果。商业现货需求质量分析工具用于确定需求陈述的语言质量指标。在模型结构之后,采用数据的交叉验证来确认模型的预测值。总而言之,结果确定要求质量确实是最终系统运营性能的预测因素;由此产生的统计模型可以根据成功运行性能的可能性通知要求决策。

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