@inproceedings{5a5a22f2164349ea8055e081017b68fc,
title = "Environment-Driven Abstraction Identification for Requirements-Based Testing",
abstract = "Abstractions are significant domain terms that have assisted in requirements elicitation and modeling. To extend the assistance towards requirements validation, we present in this paper an automated approach to identifying the abstractions for supporting requirements-based testing. We select relevant Wikipedia pages to serve as a domain corpus that is independent from any specific software system. We further define five novel patterns based on part-of-speech tagging and dependency parsing, and frame our candidate abstractions in the form of pairs for better testability. We evaluate our approach with six software systems in two application domains: Electronic health records and Web conferencing. The results show that our abstractions are more accurate than those generated by two of the state-of-the-art techniques. Initial findings also indicate our abstractions' capabilities of revealing bugs and matching the environmental assumptions created manually.",
keywords = "Abstractions, Environmental assumptions, Natural language, Requirements-based testing",
author = "Zedong Peng and Prachi Rathod and Nan Niu and Tanmay Bhowmik and Hui Liu and Lin Shi and Zhi Jin",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 29th IEEE International Requirements Engineering Conference, RE 2021 ; Conference date: 20-09-2021 Through 24-09-2021",
year = "2021",
doi = "10.1109/RE51729.2021.00029",
language = "English",
series = "Proceedings of the IEEE International Conference on Requirements Engineering",
publisher = "IEEE Computer Society",
pages = "245--256",
editor = "Ana Moreira and Kurt Schneider and Michael Vierhauser and Jane Cleland-Huang",
booktitle = "Proceedings - 29th IEEE International Requirements Engineering Conference, RE 2021",
address = "United States",
}