Replication in Requirements Engineering: the NLP for RE Case
Sallam Abualhaija, F. Ba\c{S}Ak Aydemir, Fabiano Dalpiaz, Davide, Dell'Anna, Alessio Ferrari, Xavier Franch, Davide Fucci

TL;DR
This paper introduces the ID-Card artifact to improve replication efforts in NLP for Requirements Engineering by providing structured summaries of research papers, addressing challenges like heterogeneity and reporting issues.
Contribution
The study presents the design and structure of the ID-Card, a novel artifact aimed at facilitating replication and understanding in NLP for RE research.
Findings
Identified challenges in data annotation and tool reconstruction for replication.
Reviewed state-of-the-art NLP for RE studies and extracted key replication information.
Proposed the ID-Card as a structured summary tool to support replication efforts.
Abstract
[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…
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Taxonomy
TopicsSoftware Engineering Techniques and Practices · Software Engineering Research · Software System Performance and Reliability
