Replication in Requirements Engineering: the NLP for RE Case
arxiv(2023)
摘要
[Context]} Natural language processing (NLP) techniques have been widely
applied in the requirements engineering (RE) field to support tasks such as
classification and ambiguity detection. Despite its empirical vocation, RE
research has given limited attention to replication of NLP for RE studies.
Replication is hampered by several factors, including the context specificity
of the studies, the heterogeneity of the tasks involving NLP, the tasks'
inherent hairiness, and, in turn, the heterogeneous reporting structure.
[Solution] To address these issues, we propose a new artifact, referred to as
ID-Card, whose goal is to provide a structured summary of research papers
emphasizing replication-relevant information. We construct the ID-Card through
a structured, iterative process based on design science. [Results] In this
paper: (i) we report on hands-on experiences of replication, (ii) we review the
state-of-the-art and extract replication-relevant information, (iii) we
identify, through focus groups, challenges across two typical dimensions of
replication: data annotation and tool reconstruction, and (iv) we present the
concept and structure of the ID-Card to mitigate the identified challenges.
[Contribution] This study aims to create awareness of replication in NLP for
RE. We propose an ID-Card that is intended to foster study replication, but can
also be used in other contexts, e.g., for educational purposes.
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