  The agent-based modeling and simulation (ABMS) paradigm has been used to
analyze, reproduce, and predict phenomena related to many application areas.
Although there are many agent-based platforms that support simulation
development, they rely on programming languages that require extensive
programming knowledge. Model-driven development (MDD) has been explored to
facilitate simulation modeling, by means of high-level modeling languages that
provide reusable building blocks that hide computational complexity, and code
generation. However, there is still limited knowledge of how MDD approaches to
ABMS contribute to increasing development productivity and quality. We thus in
this paper present an empirical study that quantitatively compares the use of
MDD and ABMS platforms mainly in terms of effort and developer mistakes. Our
evaluation was performed using MDD4ABMS-an MDD approach with a core and
extensions to two application areas, one of which developed for this study-and
NetLogo, a widely used platform. The obtained results show that MDD4ABMS
requires less effort to develop simulations with similar (sometimes better)
design quality than NetLogo, giving evidence of the benefits that MDD can
provide to ABMS.
