Anaphoric Ambiguity Resolution in Software Requirement Texts
Küçük Resim Yok
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
In requirements engineering (RE), anaphoric ambiguity is a frequent cause of misunderstandings. It can have a detrimental effect on the quality of requirements and jeopardize the success of a project. If stakeholders of the system, such as testers, developers, or customers, have different understandings or interpretations of software requirements, the system may not be accepted during customer validation. Despite its significance, there has been limited investigation into anaphoric ambiguity in RE. However, focusing on both recognizing and solving uncertainty can be more advantageous than just identifying it. Therefore we investigated the effectiveness of various QA learning techniques including encoder-based and text generation-based NLP models for two goals. We conduct detailed numerical experiments using various transformer models on two public requirements datasets and one generic dataset. Our results indicated that our QA architecture exhibits superior performance compared to baseline models in detecting ambiguity as well as resolving anaphora in contrast to other baseline approaches. We showed that our developed architecture can automatically support requirement development to minimize interpretation risk between stakeholders. © 2023 IEEE.
Açıklama
Ankura;IEEE Dataport
2023 IEEE International Conference on Big Data, BigData 2023 -- 15 December 2023 through 18 December 2023 -- -- 196820
2023 IEEE International Conference on Big Data, BigData 2023 -- 15 December 2023 through 18 December 2023 -- -- 196820
Anahtar Kelimeler
Ambiguity, Anaphora Resolution, Requirements Engineering, Transformers, Learning Systems, Ambiguity, Ambiguity Resolution, Anaphora Resolution, Learning Techniques, Numerical Experiments, Requirement Engineering, Software Requirements, Text Generations, Transformer, Uncertainty, Requirements Engineering
Kaynak
Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
WoS Q Değeri
Scopus Q Değeri
N/A
