In requirement engineering (RE) for agile software development, the Class-Responsibility-Collaborator (CRC) models are used as important brainstorming tool. However, manual generation of such CRC models by analyzing the requirements is a difficult and time-consuming task due to ambiguity and informal nature of natural languages-based software requirements. This paper introduces an improved requirement engineering technique based on CRC models that can help in specifying and analyzing software requirements in a better and faster way and curtailing difficulties associated with the traditional RE analysis technique. The proposed technique employs Semantics of Business Vocabulary and Rules (SBVR) to capture and specify software requirements in a controlled natural language. The SBVR representation is processed to extract object-oriented information and map the extracted information to CRC models in both textual and visual form. The proposed approach is implemented as an Eclipse plugin prototype SBVR2CRC as a proof of concept and the results of the experiments validate the effectiveness of the presented approach. Results show that such automated approach not only saves certain time and effort but also assists in generation of better CRC models and simplifies the CRC models based agile software development.
CITATION STYLE
Afreen, H., & Farooq, U. (2020). An Intelligent Approach for CRC Models Based Agile Software Requirement Engineering Using SBVR. In Communications in Computer and Information Science (Vol. 1198, pp. 372–384). Springer. https://doi.org/10.1007/978-981-15-5232-8_32
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