Completeness is one of the most important attributes of software requirement specifications. Unfortunately, incompleteness is meanwhile one of the most difficult problems to detect. Some approaches have been proposed to detect missing requirements based on the requirement-oriented domain model. However, this kind of models are lacking for lots of domains. Fortunately, the domain models constructed for different purposes can usually be found online. This raises a question: whether or not these domain models are helpful in finding the missing functional information in requirement specification? To explore this question, we design and conduct a preliminary study by computing the overlapping rate between the entities in domain models and the concepts of natural language software requirements and then digging into four regularities of the occurrence of these entities(concepts) based on two example domains. The usefulness of these regularities, especially the one based on our proposed metric AHME (with F2 gains of 146% and 223% on the two domains than without any regularity), has been shown in experiments.
翻译:完整是软件要求规格中最重要的属性之一。 不幸的是,不完善是同时最困难的问题之一,需要检测的问题之一。已经提出了一些方法,以根据面向要求的域模型来发现缺失的要求。然而,许多领域缺乏这种模型。幸运的是,为不同目的建造的域模型通常可以在网上找到。这提出了一个问题:这些域模型是否有助于在要求规格中找到缺失的功能信息?为了探讨这一问题,我们设计和进行一项初步研究,计算域模型实体与自然语言软件要求概念之间的重叠率,然后根据两个示例领域挖掘出这些实体(概念)的四种规律。这些规律,特别是以我们提议的AHME指标为基础的常规(在两个领域获得146%的F2收益,在两个领域获得223%的F2收益,而不是任何常规性)在实验中已经显示出了作用。