Classification of Testable and Valuable User Stories by using Supervised Machine Learning Classifiers

Ishan Mani Subedi, Maninder Singh, Vijayalakshmi Ramasamy, Gursimran Singh Walia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Agile is one of the most widely used software development methodologies that include user stories, the smallest units semi-structured specifications to capture the requirements from a user's point of view. Despite being popular, only a little research has been done to automate the quality checking/analysis of a user story before assigning it to a sprint. In this study, we have chosen two metrics, i.e., Testable and Valuable criteria from INVEST checklist, and have applied supervised machine learning classifiers to automatically classify them. Since the industrial data collected for the research was unbalanced, we also applied data balancing techniques such as SMOTE, RUS, ROS, and Back translation (BT) to verify if they improved any classification metrics. Although we did not see any significant improvements in accuracy and precision for the classifiers after applying data balancing techniques, we noticed a significant improvement in recall values across all the classifiers. Our research provides some promising insights into how this research could be used in the software industry to automate the analysis of user stories and improve the quality of software produced.

Original languageEnglish (US)
Title of host publicationProceedings - 2021 IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages409-414
Number of pages6
ISBN (Electronic)9781665426039
DOIs
StatePublished - 2021
Externally publishedYes
Event32nd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2021 - Wuhan, China
Duration: Oct 25 2021Oct 28 2021

Publication series

NameProceedings - 2021 IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2021

Conference

Conference32nd IEEE International Symposium on Software Reliability Engineering Workshops, ISSREW 2021
Country/TerritoryChina
CityWuhan
Period10/25/2110/28/21

Keywords

  • Machine learning
  • Requirement Engineering and Quality
  • Text Augmentation
  • User Stories

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality

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