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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.
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.
13 sie 2019 · This paper reviews the state-of-the-art in verification and validation of safety-critical systems that rely on machine learning.
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.
14 sie 2019 · In this paper, we describe our ongoing endeavor to define characteristics and challenges unique to Requirements Engineering (RE) for ML-based systems. As a first step, we interviewed four data scientists to understand how ML experts approach elicitation, specification, and assurance of requirements and expectations.
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.
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.
