Gamify4LexAmb: a gamification-based approach to address lexical ambiguity in natural language requirements

Ambiguity is a common challenge in specifying natural language (NL) requirements. One of the reasons for the occurrence of ambiguity in software requirements is the lack of user involvement in requirements elicitation and inspection phases. Even if they get involved, it is hard for them to understand the context of the system, and ultimately unable to provide requirements correctly due to a lack of interest. Previously, the researchers have worked on ambiguity avoidance, detection, and removal techniques in requirements. Still, less work is reported in the literature to actively engage users in the system to reduce ambiguity at the early stages of requirements engineering. Traditionally, ambiguity is addressed during inspection when requirements are initially specified in the SRS document. Resolving or removing ambiguity during the inspection is time-consuming, costly, and laborious. Also, traditional elicitation techniques have limitations like lack of user involvement, inactive user participation, biases, incomplete requirements, etc. Therefore, in this study, we have designed a framework, ication for ical iguity (Gamify4LexAmb), for detecting and reducing ambiguity using gamification. Gamify4LexAmb engages users and identifies lexical ambiguity in requirements, which occurs in polysemy words where a single word can have several different meanings. We have also validated Gamify4LexAmb by developing an initial prototype. The results show that Gamify4LexAmb successfully identifies lexical ambiguities in given requirements by engaging users in requirements elicitation. In the next part of our research, an industrial case study will be performed to understand the effects of gamification on real-time data for detecting and reducing NL ambiguity.