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On systematically building a controlled natural language for functional requirements.

Alvaro Veizaga1, Mauricio Alferez1, Damiano Torre1

  • 1SnT Centre for Security, Reliability and Trust, University of Luxembourg, Luxembourg City, Luxembourg.

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Summary
This summary is machine-generated.

Controlled natural languages (CNLs) like Rimay help analysts write better software requirements. Rimay effectively captures 88% of natural language requirements, improving clarity and reducing ambiguity in financial domain specifications.

Keywords:
Case study researchControlled natural languageFunctional requirementsNatural language requirementsQualitative study

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Area of Science:

  • Software Engineering
  • Computational Linguistics
  • Information Systems

Background:

  • Natural language (NL) in software requirements specifications (SRSs) often suffers from vagueness, ambiguity, and incompleteness.
  • Controlled natural languages (CNLs) offer a solution by maintaining intuitive communication while preventing quality issues.

Purpose of the Study:

  • To systematically develop and evaluate a CNL, named Rimay, for writing functional requirements.
  • To provide a qualitative methodology for CNL definition applicable across information-system domains.
  • To empirically assess Rimay's expressiveness and utility in the financial domain.

Main Methods:

  • Grounded Theory was employed for the systematic development of the Rimay CNL.
  • A qualitative methodology was used for CNL definition, drawing on 15 financial domain SRSs (3215 NL requirements).
  • An industrial case study evaluated Rimay's performance on four unseen SRSs.

Main Results:

  • A CNL grammar was derived, suitable for functional requirements and adaptable to various domains.
  • Rimay demonstrated significant expressiveness, capturing an average of 88% of NL requirements statements.
  • The methodology for CNL definition is presented as generalizable across information-system domains.

Conclusions:

  • Rimay is an effective CNL for improving the quality of functional requirements in the financial sector.
  • The developed methodology provides a systematic approach to creating domain-specific CNLs.
  • CNLs like Rimay hold promise for enhancing clarity and reducing errors in software requirements engineering.