Towards a Comprehensive Ontology for Requirements Engineering for AI-Powered Systems

Eran Sadovski, Itzhak Aviv, Irit Hadar

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

Abstract

Context and motivation: Artificial intelligence (AI) provides computer systems problem-solving and decision-making features mimicking human behavior. As AI becomes widely adopted, AI-powered systems become increasingly ubiquitous. Requirements engineering (RE) is fundamental to system development, including AI-powered systems, which provide novel RE challenges. Question/problem: Developing means for addressing these challenges, which include increased need and importance of specifying and addressing social requirements, (e.g., responsibility, ethics, and trustworthiness); achieving a comprehensive understanding of all RE aspects, given the substantial growth in the diversity and complexity of requirements and the emergence of new and often contradictory ones; and, employing relevant methods and techniques that are suited for addressing these challenges. Principal ideas/results: We propose an RE4AI ontology as a first step toward addressing the above challenges. The development of the ontology was based on a meta-synthesis of relevant publications for identifying recurring themes and patterns, resulting in a set of themes categorized into RE stages, topics, stakeholders’ roles, and constraints that formed the developed ontology. Contribution: The ontology provides a systematic and unambiguous representation of the accumulated RE knowledge about the system, including requirement themes, relationships between requirements, constraints, and stakeholders needed in the RE process. This ontology provides the basis for a complete AI RE methodology (AI-REM) framework that will incorporate methods to develop and manage AI-powered system requirements.

Original languageEnglish
Title of host publicationRequirements Engineering
Subtitle of host publicationFoundation for Software Quality - 30th International Working Conference, REFSQ 2024, Proceedings
EditorsDaniel Mendez, Daniel Mendez, Ana Moreira, Ana Moreira
PublisherSpringer Science and Business Media Deutschland GmbH
Pages219-230
Number of pages12
ISBN (Print)9783031573262
DOIs
StatePublished - 2024
Event30th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2024 - Winterthur, Switzerland
Duration: 8 Apr 202412 Apr 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14588 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference30th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2024
Country/TerritorySwitzerland
CityWinterthur
Period8/04/2412/04/24

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Keywords

  • Artificial Intelligence
  • FR
  • Machine Learning
  • NFR
  • Ontology
  • RE4AI
  • Requirement Engineering

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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