Reducing ambiguities in customer requirements through historical rule-based knowledge in a small organization.

摘要

During the elicitation process the requirements for a software application are obtained from the customer. Customers often do not know how to clearly express the requirements of the application to be built, causing requirements to be ambiguous. Many studies have been found to cover different characteristics of the requirements elicitation process including methods for reducing ambiguities in requirements. The methods and findings of these studies were found to be too general when it comes to the specific domain of the requirements and knowledge about the requirements. In addition, some studies did not take into consideration the level of expertise of those users performing the process. The focus of this study is to reduce ambiguities in customer requirements for a specific domain through the use of a historical rule-based knowledge and a scripted process. Using a case study scenario, this study explores how ambiguities in customer requirements can be reduced using knowledge about specific requirements for Web-based forms. The scripted process is a step-by-step procedure utilized to guide a novice developer in reducing the ambiguities in customer requirements. The proposed rule-based knowledge encompasses requirements of previously implemented Web-based applications.;The results of this study intend to improve domain knowledge sharing between novice and expert developers and domain experts while reducing ambiguities in customer requirements. The existence of ambiguities in requirements and the lack of knowledge about the domain, between customers and the development team, provide the context in this qualitative case study. The outcome of this study demonstrates how ambiguities in requirements can be reduced and easily understood by the development team while lessening the communication gap between all people involved. The impact of this study is relatively associated with the effort and time that goes into understanding requirements and reducing ambiguities.