On Augmenting Scenario-Based Modeling with Generative AI

Fuente: arXiv
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Hauptverfasser: Harel, David, Katz, Guy, Marron, Assaf, Szekely, Smadar
Format: Preprint
Veröffentlicht: 2024
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author Harel, David
Katz, Guy
Marron, Assaf
Szekely, Smadar
author_facet Harel, David
Katz, Guy
Marron, Assaf
Szekely, Smadar
contents The manual modeling of complex systems is a daunting task; and although a plethora of methods exist that mitigate this issue, the problem remains very difficult. Recent advances in generative AI have allowed the creation of general-purpose chatbots, capable of assisting software engineers in various modeling tasks. However, these chatbots are often inaccurate, and an unstructured use thereof could result in erroneous system models. In this paper, we outline a method for the safer and more structured use of chatbots as part of the modeling process. To streamline this integration, we propose leveraging scenario-based modeling techniques, which are known to facilitate the automated analysis of models. We argue that through iterative invocations of the chatbot and the manual and automatic inspection of the resulting models, a more accurate system model can eventually be obtained. We describe favorable preliminary results, which highlight the potential of this approach.
format Preprint
id arxiv_https___arxiv_org_abs_2401_02245
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On Augmenting Scenario-Based Modeling with Generative AI
Harel, David
Katz, Guy
Marron, Assaf
Szekely, Smadar
Software Engineering
68N19
The manual modeling of complex systems is a daunting task; and although a plethora of methods exist that mitigate this issue, the problem remains very difficult. Recent advances in generative AI have allowed the creation of general-purpose chatbots, capable of assisting software engineers in various modeling tasks. However, these chatbots are often inaccurate, and an unstructured use thereof could result in erroneous system models. In this paper, we outline a method for the safer and more structured use of chatbots as part of the modeling process. To streamline this integration, we propose leveraging scenario-based modeling techniques, which are known to facilitate the automated analysis of models. We argue that through iterative invocations of the chatbot and the manual and automatic inspection of the resulting models, a more accurate system model can eventually be obtained. We describe favorable preliminary results, which highlight the potential of this approach.
title On Augmenting Scenario-Based Modeling with Generative AI
topic Software Engineering
68N19
url https://arxiv.org/abs/2401.02245