Model Description

This repository contains a fine-tuned DistilBERT model for the automated assessment of the Atomic criterion of the Quality User Story (QUS) framework.

The model performs binary text classification to determine whether a user story satisfies the Atomic criterion. Under QUS, an atomic user story should express a requirement for exactly one feature or functionality. Stories that combine multiple independent requirements within the same statement are considered violations of this criterion.

The model was developed as part of the study "Fine-Tuned DistilBERT for Automated User Story Quality Assessment", which investigates specialized encoder-based Transformer models for identifying quality violations in agile user stories.

Classification task

Input: A user story written in natural language.
Output: Binary classification indicating compliance with the Atomic criterion.
Correct: The story describes a single feature or requirement.
Incorrect: The story combines multiple distinct features or requirements.

This model is one of eight criterion-specific DistilBERT models developed for the individual quality criteria of the QUS framework.