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Information Retrieval - Based Solution for Software Requirements Classification and Mapping

机译:基于信息检索的软件需求分类和映射解决方案

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In software engineering, the process of requirements elicitation and specification is considered as a base for all other development process. This means that any fault or mistake in the requirements definition will negatively affect the whole process of software development and consequently affect the cost, time, and effort of the developers and users. Traditionally, the process of requirement elicitation and categorization was done manually and based on the experience of the developers. However, a lot of problem came up because of the absence of automatic approaches. This paper presents a novel approach to improve the process of software requirements classification and mapping. An Information Retrieval (IR) method, namely Latent Drichelt Allocation (LDA) will be used for classification process. A corpus of software requirements also will be built to be used as input space for LDA algorithm. Typically, each requirement will have a corresponding document in the corpus. We conducted two distinct experiments. The first one is to extract the topics of software requirements, and the second one is for mapping and linking any new requirement to the most existing relevant requirements. The results showed that the proposed approach overwhelmed the state-of-art approaches.
机译:在软件工程中,需求确定和规范的过程被视为所有其他开发过程的基础。这意味着需求定义中的任何错误或错误都会对软件开发的整个过程产生负面影响,从而影响开发人员和用户的成本,时间和精力。传统上,需求启发和分类过程是手动完成的,并基于开发人员的经验。但是,由于缺少自动方法,出现了很多问题。本文提出了一种新颖的方法来改进软件需求分类和映射的过程。信息检索(IR)方法,即潜在小流藻分配(LDA)将用于分类过程。还将建立一套软件需求,以用作LDA算法的输入空间。通常,每个需求在语料库中都有一个相应的文档。我们进行了两个不同的实验。第一个是提取软件需求的主题,第二个是将任何新需求映射和链接到最现有的相关需求。结果表明,所提出的方法压倒了最先进的方法。

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