Search-based requirements traceability recovery: A multi-objective approach
Search-based requirements traceability recovery: A multi-objective approach
复制标题
基于搜索的需求可追溯性恢复：多目标方法
DOI：
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发表时间：
2017
期刊：
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通讯作者：
H. Ammar
中科院分区：
文献类型：
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作者：
Adnane Ghannem;M. Hamdi;Marouane Kessentini;H. Ammar
由于需要持续更改和适应，当今的软件系统非常复杂且难以维护。软件维护中的一个挑战是自动保持需求可追溯性。生成需求可追溯性的过程是耗时且容易出错的。目前，大多数可用的工具不支持可追溯性链接的自动恢复。在某些情况下，公司会从过去的维护经验中积累变更历史。在本文中，我们认为需求的可追溯性恢复作为一个多目标的搜索问题，我们试图将每个需求分配给一个或多个软件元素（代码元素，API文档和评论），考虑到最近的变化，变化的频率，和语义之间的相似性的描述的需求和软件元素。我们使用非支配排序遗传算法（NSGA-II）找到这三个目标之间的最佳折衷。我们报告了我们在三个开源项目上的实验结果。
Software systems nowadays are complex and difficult to maintain due to the necessity of continuous change and adaptation. One of the challenges in software maintenance is keeping requirements traceability up to date automatically. The process of generating requirements traceability is time-consuming and error-prone. Currently, most available tools do not support the automated recovery of traceability links. In some situations, companies accumulate the history of changes from past maintenance experiences. In this paper, we consider requirements traceability recovery as a multi objective search problem in which we seek to assign each requirement to one or many software elements (code elements, API documentation, and comments) by taking into account the recency of change, the frequency of change, and the semantic similarity between the description of the requirement and the software element. We use the Non-dominated Sorting Genetic Algorithm (NSGA-II) to find the best compromise between these three objectives. We report the results of our experiments on three open source projects.