Abstract In the context of Model-Driven Engineering applied to video games, software models are high-level abstractions that represent source code implementations of varied content such as the stages of the game, vehicles, or enemy entities (e.g., final bosses). In this work, we present our Evolutionary Model Generation (EMoGen) approach to generate software models that are comparable in quality to the models created by human developers. Our approach is based on an evolution (mutation and crossover) and assessment cycle to generate the software models. We evaluated the software models generated by EMoGen in the Kromaia video game, which is a commercial video game released on Steam and PlayStation 4. Each model generated by EMoGen has more than 1000 model elements. The results, which compare the software models generated by our approach and those generated by the developers, show that our approach achieves results that are comparable to the ones created manually by the developers in the retail and digital versions of the video game case study. However, our approach only takes five hours of unattended time in comparison to ten months of work by the developers. We perform a statistical analysis, and we make an implementation of EMoGen readily available.

中文翻译：

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生成软件模型的进化方法：游戏软件工程中的 Kromaia 案例

摘要 在应用于视频游戏的模型驱动工程的背景下，软件模型是高级抽象，代表不同内容的源代码实现，例如游戏阶段、车辆或敌人实体（例如最终 Boss）。在这项工作中，我们提出了我们的进化模型生成 (EMoGen) 方法来生成质量与人类开发人员创建的模型相当的软件模型。我们的方法基于进化（突变和交叉）和评估周期来生成软件模型。我们评估了 EMoGen 在 Kromaia 视频游戏中生成的软件模型，这是一款在 Steam 和 PlayStation 4 上发布的商业视频游戏。 EMoGen 生成的每个模型都有 1000 多个模型元素。结果，将我们的方法生成的软件模型与开发人员生成的软件模型进行比较，结果表明我们的方法实现的结果与开发人员在零售版和数字版视频游戏案例研究中手动创建的结果相当。然而，与开发人员十个月的工作相比，我们的方法只需要五个小时的无人值守时间。我们进行了统计分析，并且使 EMoGen 的实施随时可用。