User Story Tutor (UST) to Support Agile Software Developers

TL;DR

This paper presents User Story Tutor (UST), a web application that helps agile teams improve User Stories through readability checks, effort estimation with machine learning, and usability evaluations, supporting better agile practices.

Contribution

The paper introduces UST, a novel tool combining readability analysis, effort estimation, and usability evaluation to enhance User Story creation in agile development.

Findings

UST is effective in estimating effort with machine learning.

UST received positive usability evaluations from practitioners.

UST can reliably support agile teams in writing better User Stories.

Abstract

User Stories record what must be built in projects that use agile practices. User Stories serve both to estimate effort, generally measured in Story Points, and to plan what should be done in a Sprint. Therefore, it is essential to train software engineers on how to create simple, easily readable, and comprehensive User Stories. For that reason, we designed, implemented, applied, and evaluated a web application called User Story Tutor (UST). UST checks the description of a given User Story for readability, and if needed, recommends appropriate practices for improvement. UST also estimates a User Story effort in Story Points using Machine Learning techniques. As such UST may support the continuing education of agile development teams when writing and reviewing User Stories. UST's ease of use was evaluated by 40 agile practitioners according to the Technology Acceptance Model (TAM) and AttrakDiff. The TAM evaluation averages were good in almost all considered variables. Application of the AttrakDiff evaluation framework produced similar good results. Apparently, UST can be used with good reliability. Applying UST to assist in the construction of User Stories is a viable technique that, at the very least, can be used by agile developments to complement and enhance current User Story creation.