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An Empirical Study of Comparison of Code Metric Aggregation Methods–on Embedded Software

机译:嵌入式软件中代码度量聚合方法比较的实证研究

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How to evaluate software reliability based on historical data of embedded software projects is one of the problems we have to face in practical engineering. Therefore, we establish a software reliability evaluation model based on code metrics. This evaluation technique requires the aggregation of software code metrics into project metrics. Statistical value methods, metric distribution methods, and econometric methods are commonly-used aggregation methods. What are the differences between these methods in the software reliability evaluation process, and which methods can improve the accuracy of the reliability assessment model we have established are our concerns. In view of these concerns, we conduct an empirical study on the application of software code metric aggregation methods based on actual projects. We find the distribution of code metrics for the projects under study. Using these distribution laws, we optimiz the aggregation method of code metrics and improve the accuracy of the software reliability evaluation model.
机译:如何基于嵌入式软件项目的历史数据评估软件的可靠性是我们在实际工程中必须面对的问题之一。因此,我们建立了基于代码指标的软件可靠性评估模型。这种评估技术需要将软件代码指标聚合到项目指标中。统计值方法,度量分布方法和计量经济学方法是常用的汇总方法。这些方法在软件可靠性评估过程中有什么区别,哪些方法可以提高我们已经建立的可靠性评估模型的准确性,这是我们关注的问题。鉴于这些担忧,我们对基于实际项目的软件代码度量聚合方法的应用进行了实证研究。我们找到了所研究项目的代码指标分布。利用这些分布规律,我们优化了代码量度的汇总方法,提高了软件可靠性评估模型的准确性。

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