research-article

On systematically building a controlled natural language for functional requirements

Authors:

Alvaro Veizaga,

Mauricio Alferez,

Mehrdad Sabetzadeh,

Lionel BriandAuthors Info & Claims

Empirical Software Engineering, Volume 26, Issue 4

https://doi.org/10.1007/s10664-021-09956-6

Published: 01 July 2021 Publication History

Abstract

Natural language (NL) is pervasive in software requirements specifications (SRSs). However, despite its popularity and widespread use, NL is highly prone to quality issues such as vagueness, ambiguity, and incompleteness. Controlled natural languages (CNLs) have been proposed as a way to prevent quality problems in requirements documents, while maintaining the flexibility to write and communicate requirements in an intuitive and universally understood manner. In collaboration with an industrial partner from the financial domain, we systematically develop and evaluate a CNL, named Rimay, intended at helping analysts write functional requirements. We rely on Grounded Theory for building Rimay and follow well-known guidelines for conducting and reporting industrial case study research. Our main contributions are: (1) a qualitative methodology to systematically define a CNL for functional requirements; this methodology is intended to be general for use across information-system domains, (2) a CNL grammar to represent functional requirements; this grammar is derived from our experience in the financial domain, but should be applicable, possibly with adaptations, to other information-system domains, and (3) an empirical evaluation of our CNL (Rimay) through an industrial case study. Our contributions draw on 15 representative SRSs, collectively containing 3215 NL requirements statements from the financial domain. Our evaluation shows that Rimay is expressive enough to capture, on average, 88% (405 out of 460) of the NL requirements statements in four previously unseen SRSs from the financial domain.

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Balwani STiwari SDasgupta SSharma A(2024)An Approach for Providing Recommendation for Requirements Non-Conformant with Requirement Templates (RTs)Proceedings of the 17th Innovations in Software Engineering Conference10.1145/3641399.3641412(1-11)Online publication date: 22-Feb-2024
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https://dl.acm.org/doi/10.1007/978-3-031-49266-2_27
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cover image Empirical Software Engineering

Empirical Software Engineering Volume 26, Issue 4

Jul 2021

1061 pages

ISSN:1382-3256

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© The Author(s) 2021.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 July 2021

Accepted: 26 February 2021

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Cited By

Balwani STiwari SDasgupta SSharma A(2024)An Approach for Providing Recommendation for Requirements Non-Conformant with Requirement Templates (RTs)Proceedings of the 17th Innovations in Software Engineering Conference10.1145/3641399.3641412(1-11)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3641399.3641412
Su YWan CSethi ULu SMusuvathi MNath SBaumann ACrooks NSchwarzkopf M(2023)HotGPT: How to Make Software Documentation More Useful with a Large Language Model?Proceedings of the 19th Workshop on Hot Topics in Operating Systems10.1145/3593856.3595910(87-93)Online publication date: 22-Jun-2023
https://dl.acm.org/doi/10.1145/3593856.3595910
Gentili EFalessi D(2023)Characterizing Requirements SmellsProduct-Focused Software Process Improvement10.1007/978-3-031-49266-2_27(387-398)Online publication date: 11-Dec-2023
https://dl.acm.org/doi/10.1007/978-3-031-49266-2_27
Rocha Silva T(2022)Towards a Domain-Specific Language to Specify Interaction Scenarios for Web-Based Graphical User InterfacesCompanion of the 2022 ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3531706.3536463(48-53)Online publication date: 21-Jun-2022
https://dl.acm.org/doi/10.1145/3531706.3536463

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