Classification of Natural Language Processing Techniques for
Requirements Engineering
- URL: http://arxiv.org/abs/2204.04282v1
- Date: Fri, 8 Apr 2022 20:28:00 GMT
- Title: Classification of Natural Language Processing Techniques for
Requirements Engineering
- Authors: Liping Zhao, Waad Alhoshan, Alessio Ferrari, Keletso J. Letsholo
- Abstract summary: We present our effort to synthesize and organize 57 most frequently used NLP techniques in requirements engineering.
We classify these NLP techniques in two ways: first, by their NLP tasks in typical pipelines and second, by their linguist analysis levels.
- Score: 6.099346764207287
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Research in applying natural language processing (NLP) techniques to
requirements engineering (RE) tasks spans more than 40 years, from initial
efforts carried out in the 1980s to more recent attempts with machine learning
(ML) and deep learning (DL) techniques. However, in spite of the progress, our
recent survey shows that there is still a lack of systematic understanding and
organization of commonly used NLP techniques in RE. We believe one hurdle
facing the industry is lack of shared knowledge of NLP techniques and their
usage in RE tasks. In this paper, we present our effort to synthesize and
organize 57 most frequently used NLP techniques in RE. We classify these NLP
techniques in two ways: first, by their NLP tasks in typical pipelines and
second, by their linguist analysis levels. We believe these two ways of
classification are complementary, contributing to a better understanding of the
NLP techniques in RE and such understanding is crucial to the development of
better NLP tools for RE.
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