RatKit: A Novel Methodology for Verifying, Validating, and Testing Agent-Based Simulations: the Boids Case Study


Cakirlar I., EMEK S., Bora S., Dikenelli O.

JOURNAL OF UNIVERSAL COMPUTER SCIENCE, cilt.32, sa.1, ss.133-152, 2026 (SCI-Expanded, Scopus) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 32 Sayı: 1
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3897/jucs.148927
  • Dergi Adı: JOURNAL OF UNIVERSAL COMPUTER SCIENCE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, zbMATH, Directory of Open Access Journals
  • Sayfa Sayıları: ss.133-152
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

This study introduces a novel methodology and framework for the verification, validation, and testing of agent-based simulation models: RatKit. Building on repeatable automated testing in ABMS, the present contribution significantly extends the foundation by proposing an integrated metamodel and systematic development methodology that embeds these activities throughout the simulation lifecycle. The RatKit methodology is both general, in that it applies to a wide range of agent-based simulation models using a well-defined metamodel, and comprehensive, in that it addresses the macro-level (societal), the meso-level (interaction) and the micro-level (agent) aspects of simulations. It also provides a generic infrastructure to be able to support various VV&T techniques. RatKit is designed as a general VV&T framework for all ABM frameworks. The methodology comes with a dedicated implemented framework. It is implemented by selecting the Repast ABM development framework. RatKit is demonstrated through a detailed case study of the Boids model, where the dynamics of alignment, cohesion, and separation are examined. Results from the case study show that a test-driven approach can enhance model reliability and ensure that individual agent behaviors coalesce into realistic emergent phenomena. Experiences and feedback obtained during the case studies show that developing ABM with a test-driven method based on VV&T facilitates the creation of desired models.