使用基于搜索的概念绑定方法在源代码中允许重叠边界

N. Gold, M. Harman, Zheng Li, Kiarash Mahdavi
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引用次数: 30

摘要

支持程序理解的一种方法涉及将概念绑定到源代码。以前提出的概念绑定方法强制了不重叠的边界。然而,现实世界的程序可能包含重叠的概念。本文介绍了在概念与源代码的绑定中允许边界重叠的技术。为了允许边界重叠,概念绑定问题被重新表述为搜索问题。结果表明,重叠概念绑定的搜索空间呈指数级增长,表明了基于抽样的搜索算法的适用性。采用爬坡算法和遗传算法对空间进行采样。本文报告了将这些算法应用于取自商业金融服务部门的21个COBOL II程序的实验。结果表明,遗传算法的求解结果明显优于爬山法和随机搜索法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allowing Overlapping Boundaries in Source Code using a Search Based Approach to Concept Binding
One approach to supporting program comprehension involves binding concepts to source code. Previously proposed approaches to concept binding have enforced non-overlapping boundaries. However, real-world programs may contain overlapping concepts. This paper presents techniques to allow boundary overlap in the binding of concepts to source code. In order to allow boundaries to overlap, the concept binding problem is reformulated as a search problem. It is shown that the search space of overlapping concept bindings is exponentially large, indicating the suitability of sampling-based search algorithms. Hill climbing and genetic algorithms are introduced for sampling the space. The paper reports on experiments that apply these algorithms to 21 COBOL II programs taken from the commercial financial services sector. The results show that the genetic algorithm produces significantly better solutions than both the hill climber and random search
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