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ASE 2021
Mon 15 - Fri 19 November 2021 Australia

This program is tentative and subject to change.

Wed 17 Nov 2021 21:40 - 21:50 at Kangaroo - Generation

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.

The present work is aligned with Model-Driven Engineering ideas and it considers that models represent High-Level Abstractions corresponding to a certain source code. This work deals with commercial video game development, but it is focused on Software Engineering applied to video games, or Game Software Engineering (GSE).

In our work, the term “model” refers to Software Model and should not be confused with “mesh” or “polygon mesh”, the terms used in video games and computer graphics for the visual representation of 3D geometry/shapes. Therefore, the models studied in our research represent source code implementations and are not related to 3D visual data. The following figure (included in this work) shows a representation of the architecture for Kromaia, the commercial video game case study that was used in our research, and the role of the models present in such architecture:


Past works addressed the differences between classical Software Engineering and Game Software Engineering. The works belonging to the second area were mainly focused on issues like Requirement Traceability, and some of them applied Model-Driven Engineering to video games. Such works studied the generation of source code from software models. Our work, however, explores a different direction and addresses the generation of software models. This paper claims that it is possible to produce human-competitive software models in the context of video games, with these models specifying new video game content, which is relevant to accelerate the development of video games. We present an approach that includes the encoding and manipulation of software models and uses an evolutionary algorithm to generate software models in less (unattended) time than video game developers. We evaluate the software models produced by our approach and human developers in a PlayStation 4 / PC commercial video game case study.

This program is tentative and subject to change.

Wed 17 Nov

Displayed time zone: Hobart change

21:00 - 22:00
APIzation: Generating Reusable APIs from StackOverflow Code Snippets
Research Papers
Valerio Terragni University of Auckland, Pasquale Salza University of Zurich
FIGCPS: Effective Failure-inducing Input Generation for Cyber-Physical Systems with Deep Reinforcement Learning
Research Papers
Shaohua Zhang Tianjin University, Shuang Liu Tianjin University, Jun Sun Singapore Management University, Yuqi Chen Singapore Management University, Wenzhi Huang Tianjin University, Jinyi Liu Tianjin University, Jian Liu Tianjin University, Jianye Hao Tianjin University
An evolutionary approach for generating software models: The case of Kromaia in Game Software Engineering
Journal-first Papers
Daniel Blasco SVIT Research Group. Universidad San Jorge, Jaime Font San Jorge University, Spain, Mar Zamorano SVIT Research Group. Universidad San Jorge, Carlos Cetina San Jorge University, Spain