多目标软件维护框架中类的优先排序方法

M. Mohan, D. Greer
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引用次数: 0

摘要

遗传算法在自动化软件重构中已经变得很流行,并且越来越多的人开始关注多目标方法的使用。本文研究了使用多目标遗传算法来使用专用工具MultiRefactor自动进行软件重构。该工具使用一个度量函数来度量软件系统的质量,并测试了第二个目标来度量被重构类的重要性。这个优先级目标将一组需要支持的类和一组不需要支持的类作为输入。多目标设置利用质量目标重构输入程序以提高其质量,同时也关注用户指定的类别。构建了一个实验来衡量多目标方法和替代单目标方法,后者不使用目标来衡量类的优先级。这两种方法在六个不同的开源Java程序上进行了测试。研究发现,在相同的时间内,多目标方法在所有输入中给出了更好的优先级分数,同时也提高了质量分数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Approach to Prioritize Classes in a Multi-objective Software Maintenance Framework
: Genetic algorithms have become popular in automating software refactoring and an increasing level of attention is being given to the use of multi-objective approaches. This paper investigated the use of a mul-ti-objective genetic algorithm to automate software refactoring using a purpose built tool, MultiRefactor. The tool used a metric function to measure quality in a software system and tested a second objective to measure the importance of the classes being refactored. This priority objective takes as input a set of classes to favor and, optionally, a set of classes to disfavor as well. The multi-objective setup refactors the input program to improve its quality using the quality objective, while also focusing on the classes specified by the user. An experiment was constructed to measure the multi-objective approach against the alternative mono-objective approach that does not use an objective to measure priority of classes. The two approaches were tested on six different open source Java programs. The multi-objective approach was found to give significantly better priority scores across all inputs in a similar time, while also generating improvements in the quality scores.
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