Replication in Requirements Engineering: The NLP for RE Case Visa övriga samt affilieringar
2024 (Engelska) Ingår i: ACM Transactions on Software Engineering and Methodology, ISSN 1049-331X, E-ISSN 1557-7392, Vol. 33, nr 6, artikel-id 151Artikel i tidskrift (Refereegranskat) Published
Abstract [en]
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. 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. In this article: (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. 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. © 2024 Copyright held by the owner/author(s).
Ort, förlag, år, upplaga, sidor Association for Computing Machinery (ACM), 2024. Vol. 33, nr 6, artikel-id 151
Nyckelord [en]
annotation, ID card, Natural Language Processing (NLP), replication, Requirements Engineering (RE), tool reconstruction, Employment, Iterative methods, Natural language processing systems, ID cards, Language processing, Language processing techniques, Natural language processing, Natural languages, Requirement engineering, Requirements engineering
Nationell ämneskategori
Programvaruteknik
Identifikatorer URN: urn:nbn:se:bth-26775 DOI: 10.1145/3658669 ISI: 001283366800012 Scopus ID: 2-s2.0-85198652329 OAI: oai:DiVA.org:bth-26775 DiVA, id: diva2:1887560
Ingår i projekt SERT- Software Engineering ReThought, KK-stiftelsen
Forskningsfinansiär KK-stiftelsen, 20180010 2024-08-082024-08-082025-09-30 Bibliografiskt granskad