Agile Evaluation of the Complexity of User Stories Using the Bloom's Taxonomy

Agile methodologies are increasingly adopted by companies, these follow software engineering methods based on iterative and incremental development. Among the most popular is the framework of SCRUM (1986), which is characterized by iterations, where in each iteration it is necessary to make a planning, analysis of requirements, design, coding, tests and documentation. The requirements specification in SCRUM is based on the concept of user stories (US), which are the description of a requirement written in one or two sentences using the user's natural language. An important feature of US is that they must be estimable, that is to say, it must be possible to determine the time it will take to complete it. This allows the Scrum Development Team to determine the total time of the project. However in practice, this task still has problems due to the complexity of the requirements and affects the agreement of US in each iteration. In this paper we propose a strategy to classify the US following the taxonomy of Bloom to determine the degree of its complexity and by doing so make an agile estimation of the approximate time that each one requires for its realization. We show the results obtained after the US have been classified from two projects and based on them, we propose strategies to estimate them.