基于搜索的需求跟踪恢复:一种多目标方法

Adnane Ghannem, M. Hamdi, M. Kessentini, H. Ammar
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引用次数: 7

摘要

当今的软件系统由于需要不断的变化和适应而变得复杂和难以维护。软件维护中的挑战之一是保持需求的可追溯性自动更新。生成需求可追溯性的过程既耗时又容易出错。目前,大多数可用的工具都不支持跟踪链接的自动恢复。在某些情况下,公司从过去的维护经验中积累了变更的历史。在本文中,我们将需求可追溯性恢复视为一个多目标搜索问题,在这个问题中,我们通过考虑变更的近时性、变更的频率以及需求描述和软件元素之间的语义相似性,寻求将每个需求分配给一个或多个软件元素(代码元素、API文档和注释)。我们使用非支配排序遗传算法(NSGA-II)来找到这三个目标之间的最佳折衷。我们报告我们在三个开源项目上的实验结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Search-based requirements traceability recovery: A multi-objective approach
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.
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