Predicting software stability using case-based reasoning

D. Grosser, H. Sahraoui, Petko Valtchev
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引用次数: 40

Abstract

Predicting stability in object-oriented (OO) software, i.e., the ease with which a software item can evolve while preserving its design, is a key feature for software maintenance. We present a novel approach which relies on the case-based reasoning (CBR) paradigm. Thus, to predict the chances of an OO software item breaking downward compatibility, our method uses knowledge of past evolution extracted from different software versions. A comparison of our similarity-based approach to a classical inductive method such as decision trees, is presented which includes various tests on large datasets from existing software.
使用基于案例的推理预测软件稳定性
预测面向对象(OO)软件的稳定性,也就是说,软件项目在保持其设计的同时能够进化的容易程度,是软件维护的一个关键特征。我们提出了一种基于案例推理(CBR)范式的新方法。因此,为了预测OO软件项目打破向下兼容性的可能性,我们的方法使用了从不同软件版本中提取的过去进化的知识。将我们基于相似性的方法与经典的归纳方法(如决策树)进行比较,其中包括对来自现有软件的大型数据集的各种测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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