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The prevalence and severity of persistent ambiguity in software requirements specifications: Is a special effort needed to find them?

机译:软件需求规格中持续歧义的普遍性和严重程度:是找到它们所需的特殊努力吗?

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Context and motivation: All the research in methods and tools for avoiding, detecting, and removing ambiguities in requirements specifications assumes that doing so is necessary and that the methods and tools for doing so are worth the effort to use them. Each of two attempts by de Bruijn et al. and Philippo et al. to test these assumptions empirically with a case study examined a random sampling of the ambiguities in the requirements specification for already constructed software. Each study concluded that ambiguities in the examined requirements specification did not result in any serious defects in the downstream development and seem to have been resolved through the normal multiple inspections and discussions that characterize a serious requirements engineering process. Question/problem: However, because each study examined only a small random sampling of the many ambiguities in its specification, it may have missed the rare ambiguity that causes a serious defect in the constructed software. Moreover, as a case study, its results cannot be generalized. So the unanswered questions are: (1) "How prevalent are ambiguities that cause defects?" and (2) "What kinds of defects do these ambiguities cause?" Principal idea/Goal: The research reported in this paper tried hard to falsify de Bruijn's and Philippo's result in three different case studies, each with a requirements specification and already developed software. Each study used a purposive sampling of the ambiguities in its requirements specification to find those ambiguities that are least likely to have been discussed and resolved during the inspections and discussions about the specifications in an attempt to find undetected ambiguities that caused or can cause major defects in the implemented software. The purposive sampling was to identify types of ambiguity, called persistent ambiguities of which many people are not aware; which, therefore, will not come up in any of the discussions about the requirements; and which will persist into the implementation to cause defects. After obtaining the persistent ambiguities in the project's requirements specification, we asked the project's chief requirements engineer if any of them caused or can cause serious defects in the project's software. Conclusion/Contribution: For the three projects, none of the sampled ambiguities reviewed by each chief requirements engineer caused expensive damage because all of the project's requirements engineers seem to have subconsciously disambiguated the ambiguities in the same way. The first main conclusion is that persistent ambiguities remain undetected during requirements engineering and the subsequent development The second main conclusion is that a serious requirements engineering process is sufficient to cause all project stakeholders to disambiguate, consciously or not, all ambiguities, persistent or not, in a requirements specification the same way; thus, ambiguities, while present in the specification, do not cause defects in the downstream software. The third main conclusion is that the identification of persistent ambiguities in a requirements specification is potentially an effective and efficient strategy for minimizing damage caused by ambiguity precisely because of its focus on ambiguities that remain undetected due to lack of awareness. Further study is necessary to determine what factors are involved in persistent ambiguity and its prevalence, as well as its potential impacts.
机译:背景和动机:用于避免要求规格的避免,检测和消除歧义的方法和工具中的所有研究假定是必要的,并且这样做的方法和工具值得使用它们。 De Bruijn等人的两次尝试和philippo等。用案例研究经验测试这些假设,检查了已经构造的软件的要求规范中的含糊不清的随机抽样。每项研究得出结论,在审查的要求规范中的歧义并未导致下游发展中的任何严重缺陷,似乎通过了正常的多项检查和讨论,表征了严重要求工程过程。问题/问题:但是,每项研究只检查了其规范中许多歧义的小型随机抽样,因为它可能错过了在构造的软件中引起严重缺陷的罕见模糊性。此外,作为一个案例研究,其结果无法推广。因此,未答复的问题是:(1)“普遍性是造成缺陷的含糊不变?” (2)“这些含糊不清的缺陷是什么原因?”主要思想/目标:本文报告的研究难以伪造德布鲁亚恩和腓利会导致三种不同的案例研究,每个案例研究都有一个要求规范和已经开发的软件。每项研究用来在其要求规范中使用了歧义的有目的地抽样,以便在检查和讨论关于规范的情况下,寻求最不可能讨论和解决的那些模糊,以试图找到造成的未检测到或可能导致重大缺陷的未被发现的歧义实施的软件。目的采样是为了识别歧义的类型,称为持续的含糊不清的含量;因此,这将不会出现任何关于要求的讨论;它将持续到实施缺陷。在获得项目要求规范的持续歧义后,我们要求项目的首席要求工程师如果其中任何一个造成或可能导致项目软件中的严重缺陷。结论/贡献:对于三个项目,每个首席要求工程师审查的采样歧义都没有造成昂贵的损坏,因为所有项目的要求工程师似乎都以此的方式潜意地消灭了歧义。第一个主要结论是,在需求工程期间持续的歧义仍未被禁止,后续发展是第二个主要原因,这是一个严重的要求工程过程足以使所有项目利益相关者歧义,有意识地消除所有歧义,持久性,持久性需求规范相同;因此,含糊不清,虽然在规范中,但在下游软件中不会导致缺陷。第三个主要结论是,在需求规范中识别持续的歧义是可能是一种有效而有效的策略,可实现含糊不清造成的歧义造成的损害,因为它专注于由于缺乏意识而持续未被发现的歧义。进一步的研究是必要的,以确定有什么因素涉及持续的歧义及其流行,以及其潜在的影响。

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