Attributes-Based Decision Making for Selection of Requirement Elicitation Techniques Using the Analytic Network Process

Jinyu Li, Asif Ullah, Jun Li, Shah Nazir, Habib Ullah Khan, Hanif Ur Rehman and Amin Ul Haq

Mathematical Problems in Engineering, 2020, vol. 2020, 1-13

Abstract:

Requirement engineering is the first phase of software engineering. In requirement engineering, the first phase is requirement elicitation (RE), which is the most critical and error-prone activity. In this phase, the requirements are extracted from various sources; after extraction, they are analyzed and documented for a specific purpose of software development. In RE, process requirements from stakeholders are gathered, upon which the entire software product failure and success are dependent. In order to accomplish the goal of requirement elicitation, various techniques are used. However, the selection of these techniques is a very challenging task, as one technique may suit a situation but may not be suited for other situations. Besides this, project attributes such as documentation culture of organization, degree of relationship among stakeholders, and familiarity to domain also have a great impact on the process of technique selection. The reason is that there is no empirical value of the techniques that provide help in techniques selection to analyze the basis software project attributes. This study proposed the analytic network process, which is one of the multicriteria decision making processes for the elicitation technique selection process with respect to criterion attributes of project. The motivation toward the use of the ANP approach for the selection of requirement selection technique is that there are dependencies existing among attributes of the project elements. So, the ANP approach is capable of dealing with such situations where dependencies and complexity occur. Results of the proposed study demonstrate that the technique helps in complex situations where decision making is difficult based on the alternatives.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:2156023

DOI: 10.1155/2020/2156023

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