Standard
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements. /
Ezzini, Saad; Abualhaija, Sallam; Arora, Chetan et al.
ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ed. / Abhik Roychoudhury; Cristian Cadar; Miryung Kim. Association for Computing Machinery (ACM), 2022. p. 1677-1681 (ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Ezzini, S, Abualhaija, S, Arora, C & Sabetzadeh, M 2022,
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements. in A Roychoudhury, C Cadar & M Kim (eds),
ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Association for Computing Machinery (ACM), pp. 1677-1681.
https://doi.org/10.1145/3540250.3558928
APA
Ezzini, S., Abualhaija, S., Arora, C., & Sabetzadeh, M. (2022).
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements. In A. Roychoudhury, C. Cadar, & M. Kim (Eds.),
ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 1677-1681). (ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering). Association for Computing Machinery (ACM).
https://doi.org/10.1145/3540250.3558928
Vancouver
Ezzini S, Abualhaija S, Arora C, Sabetzadeh M.
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements. In Roychoudhury A, Cadar C, Kim M, editors, ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Association for Computing Machinery (ACM). 2022. p. 1677-1681. (ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering). doi: 10.1145/3540250.3558928
Author
Ezzini, Saad ; Abualhaija, Sallam ; Arora, Chetan et al. /
TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements. ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. editor / Abhik Roychoudhury ; Cristian Cadar ; Miryung Kim. Association for Computing Machinery (ACM), 2022. pp. 1677-1681 (ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).
Bibtex
@inproceedings{9ee7d6c9af0d414faf6bf5e7d6b02ed6,
title = "TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements",
abstract = "We introduce TAPHSIR - a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5902117).",
keywords = "Ambiguity, BERT, Machine Learning, Natural Language Processing, Natural-language Requirements, Requirements Engineering",
author = "Saad Ezzini and Sallam Abualhaija and Chetan Arora and Mehrdad Sabetzadeh",
year = "2022",
month = nov,
day = "7",
doi = "10.1145/3540250.3558928",
language = "English",
series = "ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering",
publisher = "Association for Computing Machinery (ACM)",
pages = "1677--1681",
editor = "Abhik Roychoudhury and Cristian Cadar and Miryung Kim",
booktitle = "ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering",
address = "United States",
}
RIS
TY - GEN
T1 - TAPHSIR: towards AnaPHoric ambiguity detection and ReSolution in requirements
AU - Ezzini, Saad
AU - Abualhaija, Sallam
AU - Arora, Chetan
AU - Sabetzadeh, Mehrdad
PY - 2022/11/7
Y1 - 2022/11/7
N2 - We introduce TAPHSIR - a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5902117).
AB - We introduce TAPHSIR - a tool for anaphoric ambiguity detection and anaphora resolution in requirements. TAPHSIR facilities reviewing the use of pronouns in a requirements specification and revising those pronouns that can lead to misunderstandings during the development process. To this end, TAPHSIR detects the requirements which have potential anaphoric ambiguity and further attempts interpreting anaphora occurrences automatically. TAPHSIR employs a hybrid solution composed of an ambiguity detection solution based on machine learning and an anaphora resolution solution based on a variant of the BERT language model. Given a requirements specification, TAPHSIR decides for each pronoun occurrence in the specification whether the pronoun is ambiguous or unambiguous, and further provides an automatic interpretation for the pronoun. The output generated by TAPHSIR can be easily reviewed and validated by requirements engineers. TAPHSIR is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5902117).
KW - Ambiguity
KW - BERT
KW - Machine Learning
KW - Natural Language Processing
KW - Natural-language Requirements
KW - Requirements Engineering
U2 - 10.1145/3540250.3558928
DO - 10.1145/3540250.3558928
M3 - Conference contribution/Paper
T3 - ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
SP - 1677
EP - 1681
BT - ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
A2 - Roychoudhury, Abhik
A2 - Cadar, Cristian
A2 - Kim, Miryung
PB - Association for Computing Machinery (ACM)
ER -
