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8 lut 2024 · Analyzing, identifying, and classifying nonfunctional requirements from requirement documents is time-consuming and challenging. Machine learning-based approaches have been proposed to...
26 paź 2022 · A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studies that incorporate ML and natural language processing (NLP) into demand elicitation.
15 lut 2024 · Total sixty one studies have reported in systematic review that adopted automated techniques for requirements classification. Out of 61 studies, 25 studies have used machine learning techniques, 21 studies have adopted deep learning and 9 studies have utilized transfer learning based models.
3 paź 2022 · We first review the literature on requirements engineering for machine learning, and then go through the collaborative requirements analysis process step-by-step.
14 sie 2019 · Our main findings are that requirements engineers need to be aware of new requirements types introduced by the ML paradigm, e.g., explainability and freedom from discrimination, and they need to understand quantitative ML measures to specify good func-tional requirements.
A growing trend in requirements elicitation is the use of machine learning (ML) techniques to automate the cumbersome requirement handling process. This literature review summarizes and analyzes studiesthat incorporate ML and natural language processing (NLP) into demand elicitation.
1 sie 2022 · This paper aims to provide an overview of the requirements engineering process for machine learning applications in terms of cross domain collaborations, and goes through the collaborative requirements analysis process step-by-step.
