User Story Extraction from Online News with FeatureBased and Maximum Entropy Method for Software Requirements Elicitation

Abstract

Software requirements query is the first stage in software requirements engineering. Elicitation is the process of identifying software requirements from various sources such as interviews with resource persons, questionnaires, document analysis, etc. The user story is easy to adapt according to changing system requirements. The user story is a semi-structured language because the compilation of user stories must follow the syntax as a standard for writing features in agile software development methods. In addition, user story also easily understood by end-users who do not have an information technology background because they contain descriptions of system requirements in natural language. In making user stories, there are three aspects, namely the who aspect (actor), what aspect (activity), and the why aspect (reason). This study proposes the extraction of user stories consisting of who and what aspects of online news sites using feature extraction and maximum entropy as a classification method. The systems analyst can use the actual information related to the lessons obtained in the online news to get the required software requirements. The expected result of the extraction method in this research is to produce user stories relevant to the software requirements to assist systems analysts in generating requirements. This proposed method shows that the average precision and recall are 98.21% and 95.16% for the who aspect; 87,14% and 87,50% for what aspects; 81.21% and 78.60% for user stories. Thus, this result suggests that the proposed method generates user stories relevant to functional software.