MAPE-K Loop-Based Goal Model Generation Using Generative AI
Hiroyuki Nakagawa, Shinichi Honiden
Abstract
Goal modeling constitutes a systematic modeling of representation, specifically crafted to capture and depict stakeholders' intentions, desires, and objectives. Notwithstanding its importance, describing the entire scope of goals to be achieved remains a complex task. To address this challenge, we propose a semi-automatic goal model generation process. The feature of the process lies in its use of a generative AI based on the MAPE-K loop mechanism. We conducted two case studies that built goal models using this proposed process. The results demonstrate that our process, grounded on the MAPE-K loop mechanism, efficiently aids goal model construction.
Topics & Concepts
Computer scienceGenerative grammarRepresentation (politics)Scope (computer science)Process (computing)Generative modelArtificial intelligenceTask (project management)Loop (graph theory)Machine learningFeature (linguistics)Mechanism (biology)Process modelingData miningWork in processEngineeringMathematicsSystems engineeringLawPoliticsPolitical scienceEpistemologyOperating systemPhilosophyLinguisticsProgramming languageOperations managementCombinatoricsModel-Driven Software Engineering TechniquesAdvanced Software Engineering MethodologiesSoftware Engineering Techniques and Practices