MEnDiGa: A Minimal Engine for Digital Games

Abstract EN

Game engines generate high dependence of developed games on provided implementation resources.

Feature modeling is a technique that captures commonalities and variabilities results of domain analysis to provide a basis for automated configuration of concrete products.

This paper presents the Minimal Engine for Digital Games (MEnDiGa), a simplified collection of game assets based on game features capable of building small and casual games regardless of their implementation resources.

It presents minimal features in a representative hierarchy of spatial and game elements along with basic behaviors and event support related to game logic features.

It also presents modules of code to represent, interpret, and adapt game features to provide the execution of configured games in multiple game platforms.

As a proof of concept, a clone of the Doodle Jump game was developed using MEnDiGa assets and compared with original game version.

As a result, a new G-factor based approach for game construction is provided, which is able to separate the core of game elements from the implementation itself in an independent, reusable, and large-scale way.