Ambiguous requirements: A semi-automated approach to identify and clarify ambiguity in large-scale projects. (November 2020)

• Record Type: Journal Article
• Authors: Asadabadi, Mehdi Rajabi; Saberi, Morteza; Zwikael, Ofer; Chang, Elizabeth
• Is Part Of: Computers & industrial engineering. Volume 149(2020)
• Publication Date: 2020-11
• Subjects: Fuzzy set theory -- NLP -- Soft computing -- Requirement specification -- Procurement projects; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2020.106828
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Ambiguity in setting product requirements is a major problem in large scale projects. This problem often leads to poor project selection decisions. We utilise NLP in combination with fuzzy set theory to resolve such ambiguity. We illustrate how the proposed approach can address the requirement ambiguity problem in projects. Abstract: In large-scale projects, the client defines a set of product requirements, which the provider is then expected to deliver within the agreed time, cost and scope. If a client sets ambiguous requirements for the project, this may result in the receipt of an unsatisfactory product. Therefore, reducing ambiguity in product requirements by the client is a critical success factor. Despite its significance and regular occurrence, the requirement ambiguity problem has not yet received a methodological solution that can fit large-scale projects, which commonly include a great number of requirements. This paper proposes a semi-automated approach, which combines natural language processing (NLP) to identify ambiguous terms and statements and a soft computing technique to specify these terms using fuzzy set theory. This work contributes to the current literature on requirement specification by highlighting a line of research which paves the way to leverage the applications of advanced tools to allow the clarification of ambiguous requirements in large-scale projects.