A Fuzzy Logic-Based System for Enhancing Scrum Method
In this paper, we propose a decision support system for enhancing scrum methodology based on fuzzy logic. Scrum is a very popular agile methodology within the software and product development. In the basic scrum, requirements that describe a certain task do not have a clear interpretation. Also, the traditional model does not take into account the experience of the developers nor the logical dependencies of input variables. Fuzzy inference is particularly useful for this purpose, because it incorporates logic in inference process and inputs are presented using linguistic quantifiers. The proposed system consists of three main components: a fuzzy inference system, an aggregation operator and a feedback function. The aggregation function is used to aggregate task predictions in a single value that uniquely represent a specific task, while a feedback is employed to adjust an input variable to improve system performance. Furthermore, the proposed system is simulated with randomly generated inputs in order to analyse its behaviour. The predictions of the system are more accurate and with smaller deviation in the final iterations.
JEL Classification: C63, D81, L86
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