research-article

Hacking an Ambiguity Detection Tool to Extract Variation Points: an Experience Report

Authors:

Alessandro Fantechi,

Alessio Ferrari,

Stefania Gnesi,

Laura SeminiAuthors Info & Claims

VAMOS '18: Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive Systems

Pages 43 - 50

https://doi.org/10.1145/3168365.3168381

Published: 07 February 2018 Publication History

Abstract

Natural language (NL) requirements documents can be a precious source to identify variability information. This information can be later used to define feature models from which different systems can be instantiated. In this paper, we are interested in validating the approach we have recently proposed to extract variability issues from the ambiguity defects found in NL requirement documents. To this end, we single out ambiguities using an available NL analysis tool, QuARS, and we classify the ambiguities returned by the tool by distinguishing among false positives, real ambiguities, and variation points.

We consider three medium sized requirement documents from different domains, namely, train control, social web, home automation. We report in this paper the results of the assessment. Although the validation set is not so large, the results obtained are quite uniform and permit to draw some interesting conclusions.

Starting from the results obtained, we can foresee the tailoring of a NL analysis tool for extracting variability from NL requirement documents.

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Cited By

Kato TMasuda STsuda K(2024)Design and construction of requirement specifications ambiguity detection support method2024 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW60967.2024.00033(109-115)Online publication date: 27-May-2024
https://doi.org/10.1109/ICSTW60967.2024.00033
Kato TMasuda S(2023)Improvement of Extraction Accuracy of Ambiguous Expressions in Requirement Specifications by Using a Dictionary Focusing on Compound Sentences複文に着目した辞書による要求仕様書の曖昧表現抽出精度の向上IEEJ Transactions on Electronics, Information and Systems10.1541/ieejeiss.143.810143:8(810-818)Online publication date: 1-Aug-2023
https://doi.org/10.1541/ieejeiss.143.810
Fantechi AGnesi SLivi SSemini LMousavi MSchobbens P(2021)A spaCy-based tool for extracting variability from NL requirementsProceedings of the 25th ACM International Systems and Software Product Line Conference - Volume B10.1145/3461002.3473074(32-35)Online publication date: 6-Sep-2021
https://dl.acm.org/doi/10.1145/3461002.3473074
Show More Cited By

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VAMOS '18: Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive Systems

February 2018

128 pages

ISBN:9781450353984

DOI:10.1145/3168365

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Universidad Politécnica de Madrid
URJC: Rey Juan Carlos University

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Association for Computing Machinery

New York, NY, United States

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Published: 07 February 2018

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VAMOS 2018

VAMOS 2018: 12th International Workshop on Variability Modelling of Software-Intensive Systems

February 7 - 9, 2018

Madrid, Spain

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VAMOS '18 Paper Acceptance Rate 15 of 34 submissions, 44%;

Overall Acceptance Rate 66 of 147 submissions, 45%

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Cited By

Kato TMasuda STsuda K(2024)Design and construction of requirement specifications ambiguity detection support method2024 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)10.1109/ICSTW60967.2024.00033(109-115)Online publication date: 27-May-2024
https://doi.org/10.1109/ICSTW60967.2024.00033
Kato TMasuda S(2023)Improvement of Extraction Accuracy of Ambiguous Expressions in Requirement Specifications by Using a Dictionary Focusing on Compound Sentences複文に着目した辞書による要求仕様書の曖昧表現抽出精度の向上IEEJ Transactions on Electronics, Information and Systems10.1541/ieejeiss.143.810143:8(810-818)Online publication date: 1-Aug-2023
https://doi.org/10.1541/ieejeiss.143.810
Fantechi AGnesi SLivi SSemini LMousavi MSchobbens P(2021)A spaCy-based tool for extracting variability from NL requirementsProceedings of the 25th ACM International Systems and Software Product Line Conference - Volume B10.1145/3461002.3473074(32-35)Online publication date: 6-Sep-2021
https://dl.acm.org/doi/10.1145/3461002.3473074
Fantechi AGnesi SSemini L(2019)Applying the QuARS Tool to Detect VariabilityProceedings of the 23rd International Systems and Software Product Line Conference - Volume B10.1145/3307630.3342388(29-32)Online publication date: 9-Sep-2019
https://dl.acm.org/doi/10.1145/3307630.3342388
Li YSchulze SSaake G(2018)Reverse engineering variability from requirement documents based on probabilistic relevance and word embeddingProceedings of the 22nd International Systems and Software Product Line Conference - Volume 110.1145/3233027.3233033(121-131)Online publication date: 10-Sep-2018
https://dl.acm.org/doi/10.1145/3233027.3233033
Fantechi AFerrari AGnesi SSemini L(2018)Requirement Engineering of Software Product Lines: Extracting Variability Using NLP2018 IEEE 26th International Requirements Engineering Conference (RE)10.1109/RE.2018.00053(418-423)Online publication date: Aug-2018
https://doi.org/10.1109/RE.2018.00053

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