Reducing Requirements Ambiguity via Gamification: Comparison with Traditional Techniques

Abstract

Requirements elicitation is one of the most significant activities of requirements engineering (RE) process. Poorly specified requirements can lead to a failed project. Various elicitation techniques are used to elicit requirements from the users and other stakeholders, each having its own pros and cons. Lack of user engagement, less user involvement, textual nature of the requirements, time taking process are some of the major problems that make it difficult to perform elicitation via traditional techniques. Moreover, these problems further create other challenges such as ambiguity, inconsistency, and incompleteness in requirements. Currently, researchers have focused on reducing ambiguity in requirements with the help of different techniques such as natural language processing techniques, requirement templates, and formal methods; however, these techniques work on reducing ambiguity during specification or from specified requirements. One of the “young’ and exciting way of engaging users in requirements elicitation of a system is “Gamification’, which helps in user engagement into the system. We intend to discover how gamification helps in reducing ambiguity by engaging stakeholders in an interactive manner. In this review study, we have reviewed traditional techniques used to detect and reduce requirements ambiguity. On the contrary, we have also presented the significance of gamification in requirements elicitation and the popular but effective game elements used in similar systems. Furthermore, this study highlights the significance of using gamification in requirements elicitation, which is beneficial to software development team as well as the users involved in the system.

A Systematic Literature Review on Using Natural Language Processing in Software Requirements Engineering

“…Software Requirements Engineering (SRE) includes essential activities such as elicitation, specification, modeling, and validation, which are important for ensuring good final software quality. Traditionally, these activities have relied heavily on manual interpretation and analysis, often leading to ambiguity, misunderstanding, and inefficiency [1,2]. Natural language is prone to ambiguity, leading to incompleteness and inconsistencies in requirement specifications.…”