Model-Driven Software Product Line Engineering of AI-Based Applications for Achieving Sustainable Development Goals: Vision Paper

Achieving the Sustainable Development Goals (SDGs) set by the United Nations requires innovative solutions to address the related complex and interconnected challenges. The application of AI has demonstrated the potential to significantly contribute to these efforts by providing advanced analytics and decision-making capabilities. However, integrating AI into sustainability initiatives faces several challenges, including the need for flexible and reusable solutions that can be adapted to diverse and evolving SDG contexts, as well as the challenge of making these technologies accessible to nonexpert stakeholders. This paper proposes an integrated approach that combines Model-Driven Engineering (MDE) with Software Product Line Engineering (SPLE) to address these challenges. The proposed process includes key activities such as domain analysis, metamodel-driven requirements specification, product derivation, and AI model training. This approach aims to automate the derivation of flexible and reusable AI architectures tailored to specific SDG contexts, thus reducing the development time of AI-based software solutions for sustainability efforts.

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Published
2024-09-22
DOI
https://doi.org/10.1145/3652620.3687798
Primary Topic
Advanced Software Engineering Methodologies
Type
article
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article

Model-Driven Software Product Line Engineering of AI-Based Applications for Achieving Sustainable Development Goals: Vision Paper

Benoît Ries, Nicolas Guelfi, Tiago Sousa
Advanced Software Engineering Methodologies
article

Model-Driven Software Product Line Engineering of AI-Based Applications for Achieving Sustainable Development Goals: Vision Paper

Benoît Ries, Nicolas Guelfi, Tiago Sousa
article en

Abstract

Achieving the Sustainable Development Goals (SDGs) set by the United Nations requires innovative solutions to address the related complex and interconnected challenges. The application of AI has demonstrated the potential to significantly contribute to these efforts by providing advanced analytics and decision-making capabilities. However, integrating AI into sustainability initiatives faces several challenges, including the need for flexible and reusable solutions that can be adapted to diverse and evolving SDG contexts, as well as the challenge of making these technologies accessible to nonexpert stakeholders. This paper proposes an integrated approach that combines Model-Driven Engineering (MDE) with Software Product Line Engineering (SPLE) to address these challenges. The proposed process includes key activities such as domain analysis, metamodel-driven requirements specification, product derivation, and AI model training. This approach aims to automate the derivation of flexible and reusable AI architectures tailored to specific SDG contexts, thus reducing the development time of AI-based software solutions for sustainability efforts.

University of Luxembourg (LU)
Openalex Percentile: Top 83%
Advanced Software Engineering Methodologies
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Model-Driven Software Product Line Engineering of AI-Based Applications for Achieving Sustainable Development Goals: Vision Paper — Benoît Ries, Nicolas Guelfi, et al. · (2024) | TGRS Research Map | TGRS