TOOL FOR ESTIMATING USER STORIES ASSOCIATED WITH NON-FUNCTIONAL REQUIREMENTS
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Abstract
One of the initial steps in developing any software product is defining its functional and non-functional requirements, the latter also known as quality requirements. Several stakeholders are involved in this process. However, estimating the effort needed to implement these requi rements, particularly the quality ones, is a complex task. To overcome this challenge, we present Story Points Predictor (SPP), a tool for predicting the effort required to implement quality requirements using artificial intelligence techniques. Based on historical data, SPP estimates the size of the requirements and classifies them into three groups: small, medium, and large. Development teams can use SPP to complement their effort estimation process for requirements. Experimental results show that SPP has a 72% accuracy.
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References
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