Automatically Classifying Functional and Non-functional Requirements Using Supervised Machine Learning
RE 2017
Pages: 490 - 495
Published: Sep 1, 2017
Abstract
In this paper, we take up the second RE17 data challenge: the identification of requirements types using the Quality attributes null dataset provided. We studied how accurately we can automatically classify requirements as functional (FR) and non-functional (NFR) in the dataset with supervised machine learning. Furthermore, we assessed how accurately we can identify various types of NFRs, in particular usability, security, operational, and...
Paper Details
Title
Automatically Classifying Functional and Non-functional Requirements Using Supervised Machine Learning
Published Date
Sep 1, 2017
Pages
490 - 495
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