不确定性下的软件重构:一种健壮的多目标方法

Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation Pub Date : 2014-07-12 DOI:10.1145/2598394.2598499

Mohamed Wiem Mkaouer, M. Kessentini, Slim Bechikh, M. Cinnéide, K. Deb

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引用次数: 16

摘要

重构大型系统涉及到几个不确定性来源，这些不确定性来源与要纠正的代码气味的严重程度以及气味所在的类的重要性有关。由于软件开发的动态性，这些值在实践中无法准确确定，从而导致重构序列缺乏鲁棒性。为了解决这个问题，我们引入了一个基于NSGA-II的多目标鲁棒模型，用于软件重构问题，该模型试图在质量和鲁棒性之间找到最佳平衡点。

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Software refactoring under uncertainty: a robust multi-objective approach

Refactoring large systems involves several sources of uncertainty related to the severity levels of code smells to be corrected and the importance of the classes in which the smells are located. Due to the dynamic nature of software development, these values cannot be accurately determined in practice, leading to refactoring sequences that lack robustness. To address this problem, we introduced a multi-objective robust model, based on NSGA-II, for the software refactoring problem that tries to find the best trade-off between quality and robustness.

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Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation

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