3D游戏的行为驱动开发

IF 2.7 3区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Fernando Pastor Ricós , Beatriz Marín , I.S.W.B. Prasetya , Tanja E.J. Vos , Joseph Davidson , Karel Hovorka
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引用次数: 0

摘要

电脑3D游戏是复杂的软件环境,需要新颖的测试过程来确保高质量的标准。基于扩展现实系统的智能验证/验证(iv4XR)框架通过实现自动代理来自动化游戏测试场景,解决了这一需求。这个框架促进了复杂3D游戏(如《太空工程师》)回归测试用例的自动化。然而,使用iv4XR定义测试脚本所需的技术专长会限制开发人员和测试人员之间的无缝协作。本文报告了如何将行为驱动开发(BDD)方法与iv4XR框架集成,从而使Space Engineers背后的工业公司能够自动化回归测试。这次工业合作的成功启发了iv4XR团队整合BDD方法,以提高实验性3D游戏《lab新兵》的游戏测试自动化。此外,iv4XR框架已经通过战术编程进行了扩展,以实现空间工程师长期测试场景的自动化。这些结果强调了iv4XR框架在支持各种测试方法方面的多功能性,同时展示了BDD如何使用户能够使用全面和人类可读的语句创建,管理和执行自动化游戏测试。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Behavior Driven Development for 3D games
Computer 3D games are complex software environments that require novel testing processes to ensure high-quality standards. The Intelligent Verification/Validation for Extended Reality Based Systems (iv4XR) framework addresses this need by enabling the implementation of autonomous agents to automate game testing scenarios. This framework facilitates the automation of regression test cases for complex 3D games like Space Engineers. Nevertheless, the technical expertise required to define test scripts using iv4XR can constrain seamless collaboration between developers and testers. This paper reports how integrating a Behavior-Driven Development (BDD) approach with the iv4XR framework allows the industrial company behind Space Engineers to automate regression testing. The success of this industrial collaboration has inspired the iv4XR team to integrate the BDD approach to improve the automation of play-testing for the experimental 3D game LabRecruits. Furthermore, the iv4XR framework has been extended with tactical programming to enable the automation of long-play test scenarios in Space Engineers. These results underscore the versatility of the iv4XR framework in supporting diverse testing approaches while showcasing how BDD empowers users to create, manage, and execute automated game tests using comprehensive and human-readable statements.
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来源期刊
Data & Knowledge Engineering
Data & Knowledge Engineering 工程技术-计算机:人工智能
CiteScore
5.00
自引率
0.00%
发文量
66
审稿时长
6 months
期刊介绍: Data & Knowledge Engineering (DKE) stimulates the exchange of ideas and interaction between these two related fields of interest. DKE reaches a world-wide audience of researchers, designers, managers and users. The major aim of the journal is to identify, investigate and analyze the underlying principles in the design and effective use of these systems.
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