Investigating code fault proneness using program slicing

这个可行性研究探讨了程序片段和错误之间的关系。目的是研究是否可以使用程序片的特征来识别容易出错的代码热点。切片度量和依赖聚类用于描述软件组件中的切片。然后分析了该分量中这些切片的特征与该分量中的断层之间的关系。识别易出错代码是困难的，而且可靠的易出错预测在文献中没有广泛报道。程序切片是一种成熟的软件工程技术，用于支持已知故障的检测和纠正。一旦出现问题，切片就可以识别和提取可能导致该问题的所有语句。这段提取的代码使得识别和删除故障变得更加容易。我们建议研究切片是否也可以很好地预测尚未引起问题的潜在故障。本研究的结果将显示程序切片的使用是否可以扩展为预测易出错代码的可靠工具。我们之前的概念验证研究表明，这项研究是可行的，切片可能为断层倾向提供有价值的见解。

This feasibility study explores the relationship between program slices and faults. The aim is to investigate whether the characteristics of program slices can be used to identify fault-prone code hotspots. Slicing metrics and dependence clusters are used to characterise the slices in a software component. The relationship between the characteristics of those slices in the component and the faults in that component are then analysed. Identifying fault-prone code is difficult and reliable predictors of fault-proneness are not widely reported in the literature. Program slicing is an established software engineering technique to support the detection and correction of known faults. Once a problem has emerged, slicing enables all statements that could have caused that problem to be identified and extracted. This extracted code makes the identification and removal of the fault much easier. We propose to investigate whether slicing could also be a good predictor of latent faults that have not yet caused a problem. The results of this study will show whether the use of program slicing can be extended as a reliable tool to predict fault-prone code. Our previous proof of concept study suggests that this investigation is viable and that slicing may offer valuable insights into fault-proneness.