Abstract
Several known methods allow to estimate the overall effort(s) to be used up for the software development. The approach based on story points is preferable and quite common in the context of Sсrum agile development methodology. However, it might be rather challenging for people, who are new to this methodology or to a specific Scrum team to estimate the amount of work with story points. The proposed approach involves estimation of features on the basis of linguistic terms that are both habitual and clear for everyone. The presented fuzzy inference system (Mamdani’s model) makes it possible to calculate story points using people’s opinions expressed as sentences in natural language - the study shows empirically that beginners to Scrum methodology consider the proposed approach to be more convenient and easier in use than the ‘plain’ story points estimation. Also, four groups of people with different levels of qualification in Scrum were asked to estimate several features of a certain project using the developed approach and common story points approach to prove the relevance of the approach - it was shown that the results of basic story points estimation for Scrum experts differ slightly from the results revealed by proposed approach, while for Scrum beginners such difference is significant. To the opinion of authors, the proposed approach may allow to adapt to Scrum more smoothly, with better understanding of what is implied by story points, grasping the general idea and learning faster their use in practice. The experimental study conducted as a part of the research has shown results approaching the estimations provided by Scrum experts who have been working in real projects and making use of story points for several years. Continuation of the present work can be associated with intensive studies of more complicated methods of aggregation of the experts’ opinions, analysis of alternative representation forms of confidence degrees in estimates provided as well as the development of plugin for JIRA tracking system.
Highlights
Many software systems relate to large-scaled and rather complex products that embrace, in particular, numerous factors to monitor and control at the development stage
Fuzzy inference scheme lays both solid and transparent groundwork for converting aforesaid input information to the number of story points that can be utilized in the software project management (SPM) at a later stage
The experimental study of the proposed method has shown results approaching the estimations provided by Scrum experts who have been working in real projects and making use of story points for several years
Summary
Many software systems relate to large-scaled and rather complex products that embrace, in particular, numerous factors to monitor and control at the development stage. We consider the method of estimation with story points in the context of Scrum, an agile flexible framework to manage the process of software development. Story points may be employed as such units of measure to express an estimate of the overall effort required to fully implement a product backlog item or any other piece of work [5]. As it is noticed by Joshua Kerievsky [6], “.
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