Reference : Using Domain-specific Corpora for Improved Handling of Ambiguity in Requirements
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/46224
Using Domain-specific Corpora for Improved Handling of Ambiguity in Requirements
English
Ezzini, Saad mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
Abualhaija, Sallam mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
Arora, Chetan mailto [Deakin University]
Sabetzadeh, Mehrdad mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
Briand, Lionel mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SVV >]
May-2021
In Proceedings of the 43rd International Conference on Software Engineering (ICSE'21), Madrid 25-28 May 2021
Yes
International
43rd International Conference on Software Engineering
from 25-05-2021 to 28-05-2021
[en] Requirements Engineering ; Natural-language Requirements ; Ambiguity ; Natural Language Processing ; Corpus Generation ; Wikipedia
[en] Ambiguity in natural-language requirements is a pervasive issue that has been studied by the requirements engineering community for more than two decades. A fully manual approach for addressing ambiguity in requirements is tedious and time-consuming, and may further overlook unacknowledged ambiguity – the situation where different stakeholders perceive a requirement as unambiguous but, in reality, interpret the requirement differently. In this paper, we propose an automated approach that uses natural language processing for handling ambiguity in requirements. Our approach is based on the automatic generation of a domain-specific corpus from Wikipedia. Integrating domain knowledge, as we show in our evaluation, leads to a significant positive improvement in the accuracy of ambiguity detection and interpretation. We scope our work to coordination ambiguity (CA) and prepositional-phrase attachment ambiguity (PAA) because of the prevalence of these types of ambiguity in natural-language requirements [1]. We evaluate our approach on 20 industrial requirements documents. These documents collectively contain more than 5000 requirements from seven distinct application domains. Over this dataset, our approach detects CA and PAA with an average precision of 80% and an average recall of 89% ( 90% for cases of unacknowledged ambiguity). The automatic interpretations that our approach yields have an average accuracy of 85%. Compared to baselines that use generic corpora, our approach, which uses domain-specific corpora, has 33% better accuracy in ambiguity detection and 16% better accuracy in interpretation.
http://hdl.handle.net/10993/46224
FnR ; FNR12632261 > Mehrdad Sabetzadeh > EQUACS > Early Quality Assurance Of Critical Systems > 01/01/2019 > 31/12/2021 > 2018

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