A Bird’s Eye View of Natural Language Processing and Requirements Engineering

Abstract

Natural Language Processing (NLP) has demonstrated effectiveness in many application domains. NLP can assist software engineering by automating various activities. This paper examines the interaction between software requirements engineering (RE) and NLP. We reviewed the current literature to evaluate how NLP supports RE and to examine research developments. This literature review indicates that NLP is being employed in all the phases of the RE domain. This paper focuses on the phases of elicitation and the analysis of requirements. RE communication issues are primarily associated with the elicitation and analysis phases of the requirements. These issues include ambiguity, inconsistency, and incompleteness. Many of these problems stem from a lack of participation by the stakeholders in both phases. Thus, we address the application of NLP during the process of requirements elicitation and analysis. We discuss the limitations of NLP in these two phases. Potential future directions for the domain are examined. This paper asserts that human involvement with knowledge about the domain and the specific project is still needed in the RE process despite progress in the development of NLP systems.

Ambiguity in user stories: A systematic literature review

“…[44,45,68,71,73,74],), most studies investigate ambiguity within the scope of individual user stories or between a pair of user stories. This is in line with previous literature reviews [59,60] that observed that most of the reviewed studies aim at detecting ambiguity in single sentences rather than in fragments of text covering multiple requirements. As we demonstrated with our example in Section 2, ambiguity at all linguistic levels can depend on the scope considered.…”

“…Their review indicated that 56.72% of the reviewed studies applied ontologies to reduce ambiguity when specifying requirements. Kocerka et al [59] and Alzayed and Al-Hunaiyyan [60] performed literature reviews on the use of NLP to improve requirements quality and to automatically detect ambiguity present in requirements. An interesting finding is that most of the reviewed studies aim at detecting ambiguity in single sentences rather than in fragments of text covering multiple requirements.…”

“…As discussed in Section 3, ambiguity in requirements is not a problem that is unique to the user story technique (e.g., [34,37,60,62,63]). To get more insight into how this problem manifests itself in user stories and what possible causes and effects are, we first classified the 36 selected papers according to the linguistic level of ambiguity of the problem, as it is described in the papers, following the classification schema of Berry and Kamsties [64]:…”

Requirements Engineering: A State of Practice in Gulf Cooperation Countries

“…Although a considerable amount of research has been undertaken with the aim of designing novel improved solutions to address software development (SD) difficulties [1][2][3], it is crucial to develop an understanding of contemporary software development methods and which of them offers optimal outcomes. Past research has demonstrated that accuracy and completeness in the requirements engineering (RE) practices of developers play a significant part in the success or failure [4][5][6].…”

“…This column represents the percentage of 'yes' answers to questions for failed projects 2. This column represents the percentage of 'yes' answers to questions for successful projects 3.…”