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Estimating User Stories’ Complexity and Importance in Scrum with Bayesian Networks

  • Janeth López-MartínezEmail author
  • Reyes Juárez-Ramírez
  • Alan Ramírez-Noriega
  • Guillermo Licea
  • Raúl Navarro-Almanza
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 569)

Abstract

Planning Poker is a light-weight technique for estimating the size of user stories, in face-to-face interaction and discussions. Planning Poker is generally used with Scrum. Planning Poker has a lot of benefits, however, this method is not entirely efficient because the result is always based on the observation of an expert. This paper proposes a new model to estimate the complexity and importance of user stories based on Planning Poker in the context of Scrum. The goal of this work is to facilitate the decision-making of newbie developers when they estimate user stories’ parameters. Hence, the decision of each member would be clearer to understand than when the complexity is taken as a whole. We use a Bayesian Network to co-relate factors to have accurate in the estimation. The Bayesian Network gives the complexity of a user story, according to the Fibonacci scale used in Planning Poker.

Keywords

Planning Poker Complexity Scrum User story estimation 

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Janeth López-Martínez
    • 1
    Email author
  • Reyes Juárez-Ramírez
    • 1
  • Alan Ramírez-Noriega
    • 1
  • Guillermo Licea
    • 1
  • Raúl Navarro-Almanza
    • 1
  1. 1.Universidad Autónoma de Baja CaliforniaTijuanaMexico

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