Rule-based Ontology Framework (ROF) for Auto-Generating Requirements Specification: A Case Study


Yanuarifiani, Amarilis Putri and Chua, Fang Fang and Chan, Gaik Yee (2019) Rule-based Ontology Framework (ROF) for Auto-Generating Requirements Specification: A Case Study. Frontiers in Artificial Intelligence and Applications, 318. pp. 347-360. ISSN 0922-6389, eISSN: 1879-8314

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Building requirements specification document in semi-formal notation and natural language needs great effort from users and developers. However, the current approach to the requirements engineering process is still lacking in auto-generating model and documentation. Most approaches only focusing in building UML use cases and a brief version of Software Requirements Specification (SRS), which are not enough as a basis for the code development process. A Rule-based Ontology Framework (ROF) for AutoGenerating Requirements Specification is proposed. It is used for auto-generating requirements specifications that consist of semi-formal modeling in Business Process Model Notation (BPMN) and natural language of Software Requirements Specification (SRS) in IEEE template. This paper discusses the implementation of ROF in a requirement engineering process in a University located in Indonesia. It is applied in Lecturer Workload Management (LWM) Application, an application that summarizes lecturer workload and calculates the scores as basis for generating salary. This application was developed by the Department of Information Systems (ISD). Existing requirements engineering process mostly depend on users’ perspective which causes building the requirements documentation require much effort and do not represent the real needs of users. Thus, the requirements documents do not support the development process which causes project delay. Using ROF, the requirements engineering process becomes more effective by specifying functional requirements that represent user’s needs and produce document that is feasible to be used as a reference for the development process

Item Type: Article
Uncontrolled Keywords: Requirements ontology, auto-generate BPMN, auto-generate SRS
Subjects: H Social Sciences > HD Industries. Land use. Labor > HD101-1395.5 Land use. Land tenure
Divisions: Faculty of Computing and Informatics (FCI)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 27 Apr 2022 01:22
Last Modified: 27 Apr 2022 01:22


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