Quality in Des, Sd, and Abm: an Algorithmic Analysis of Literature

This study examines simulation quality in Modeling and Simulation (M&S) literature, focusing on Discrete Event Simulation (DES), System Dynamics (SD), and Agent-Based Modeling (ABM). To systematically identify widely adopted quality-improvement practices, a clustering analysis is applied to co-occurrence patterns in the literature. A genetic algorithm extracts the most frequently referenced and interconnected practices, forming three distinct frameworks for DES, SD, and ABM that span all key development stages. This approach highlights shared and methodology-specific practices, offering insights into how simulation quality is addressed across paradigms. By structuring these practices into coherent frameworks, the study facilitates critical examination of simulation methods and their interdependencies, providing practitioners with a reference for improving model development.