@inproceedings{fe69b3be337a44459b747f19a1b84ec1,
title = "Extracting software functional requirements from free text documents",
abstract = "The acquisition of requirements assets are important in software product line (SPL) engineering for it help enhancing the effectiveness of reuse. Traditional methods are heavily based on manual effort. This appears to be a barrier for many organizations which tend to launch a SPL. In this paper, we propose an approach to extract functional requirements by analyzing text-based software requirements specifications (SRSs). We analyze the linguistic characterizat-ion of SRSs. According to it we define extended functional requirements framework (EFRF) which consists of 10 semantic cases, then we generate converting rules. We introduce an NLP (Natural Language Process) approach to build EFRFs from documents based on the concept of EFRF and the converting rules. The extracted EFRFs are suitable for expression and modeling of functional requirements variability. We apply our method to an auto-marker software product line. The result shows the approach has high accuracy and efficiency, and the approach is readily scalable and extensible.",
keywords = "Functional requirement, Information extract, Product line, Rule-based, Variability model",
author = "Yunhe Mu and Yinglin Wang and Jianmei Guo",
year = "2009",
doi = "10.1109/ICIMT.2009.47",
language = "英语",
isbn = "9780769539225",
series = "2009 International Conference on Information and Multimedia Technology, ICIMT 2009",
pages = "194--198",
booktitle = "2009 International Conference on Information and Multimedia Technology, ICIMT 2009",
note = "2009 International Conference on Information and Multimedia Technology, ICIMT 2009 ; Conference date: 16-12-2009 Through 18-12-2009",
}