Detection of Linguistic Bad Smells in GRL Models: An NLP Approach

Nouf Alturayeif, Jameleddine Hassine

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Goal-Oriented Requirements Engineering (GORE) plays a crucial role in facilitating effective communication between stakeholders in system development. Through the use of goal models, GORE provides a structured approach for eliciting, analyzing, and managing requirements from the perspective of stakeholders' goals and intentions. However, goal models are susceptible to poor practices, called also bad smells, that may hinder the effective communication and understanding among stakeholders, potentially leading to misinterpretations and inconsistencies in requirements. In particular, goal models are prone to linguistic bad smells encompassing a spectrum of anoma-lies such as unclear or ambiguous goal statements, conflicting or contradictory requirements, and instances of misspellings. Therefore, identifying and addressing linguistic bad smells in goal models is crucial for ensuring the quality and accuracy of goal models. In this paper, we define seventeen linguistic bad smells in goal models, classified into four categories: Syntax, Semantics, Pragmatics, and Complexity. Furthermore, we provide Natural Language Processing (NLP) based detection methods for twelve specific bad smells, which we have automated to target Textual GRL (TGRL) models. The proposed approach and tool are evaluated using two TGRL models achieving an F2-Score of 0.8.

Original languageEnglish
Title of host publicationProceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages318-327
Number of pages10
ISBN (Electronic)9798350324983
DOIs
StatePublished - 2023
Event2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023 - Vasteras, Sweden
Duration: 1 Oct 20236 Oct 2023

Publication series

NameProceedings - 2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion, MODELS-C 2023

Conference

Conference2023 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems, MODELS-C 2023
Country/TerritorySweden
CityVasteras
Period1/10/236/10/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

  • Goal-Oriented Requirements Engineering (GORE)
  • Linguistic Bad Smells
  • Natural Language Processing (NLP)
  • Textual Goal-oriented Requirement Language (TGRL)

ASJC Scopus subject areas

  • Software
  • Engineering (miscellaneous)

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