A Survey of Video Game Testing

Politowski, Cristiano; Petrillo, Fábio; Guéhéneuc, Yann‐Gaël

doi:10.1109/ast52587.2021.00018

Cited by 39 publications

(13 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Second, PP’s formal models also open a wide range of practical implementations in digital games. A computational model of motivationally and experientially optimal consumable uncertainty and uncertainty reduction rates could for example be used for automated playtesting ( Politowski et al, 2022 ), experience-driven procedural content generation ( Yannakakis and Togelius, 2011 ), dynamic difficulty adjustment ( Zohaib, 2018 ), or adaptive AI NPCs ( Merrick, 2016 ).…”

Section: Discussionmentioning

confidence: 99%

Mastering uncertainty: A predictive processing account of enjoying uncertain success in video game play

Deterding

Andersen

Kiverstein³

et al. 2022

Front. Psychol.

View full text Add to dashboard Cite

Why do we seek out and enjoy uncertain success in playing games? Game designers and researchers suggest that games whose challenges match player skills afford engaging experiences of achievement, competence, or effectance—of doing well. Yet, current models struggle to explain why such balanced challenges best afford these experiences and do not straightforwardly account for the appeal of high- and low-challenge game genres like Idle and Soulslike games. In this article, we show that Predictive Processing (PP) provides a coherent formal cognitive framework which can explain the fun in tackling game challenges with uncertain success as the dynamic process of reducing uncertainty surprisingly efficiently. In gameplay as elsewhere, people enjoy doing better than expected, which can track learning progress. In different forms, balanced, Idle, and Soulslike games alike afford regular accelerations of uncertainty reduction. We argue that this model also aligns with a popular practitioner model, Raph Koster’s Theory of Fun for Game Design, and can unify currently differentially modelled gameplay motives around competence and curiosity.

show abstract

Section: Discussionmentioning

confidence: 99%

Mastering uncertainty: A predictive processing account of enjoying uncertain success in video game play

Deterding

Andersen

Kiverstein³

et al. 2022

Front. Psychol.

View full text Add to dashboard Cite

show abstract

“…Video games, aside from having code, also integrate artistic elements (sound, 2D/3D graphics, history, etc.). Also, in video games, aside of testing techniques like white-box and black-box testing, developers must assess other attributes, like experience and usability [16].…”

Section: Video Game Testingmentioning

confidence: 99%

“…Testing. In a previous work [16], we briefly discussed automated video game testing issues. According to the academic literature, the main issues are related to:…”

Section: Automated Video Gamementioning

confidence: 99%

Towards Automated Video Game Testing: Still a Long Way to Go

Politowski¹,

Guéhéneuc²,

Petrillo³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

As the complexity and scope of game development increases, playtesting remains an essential activity to ensure the quality of video games. Yet, the manual, ad-hoc nature of playtesting gives space to improvements in the process. In this paper, we investigate gaps between academic solutions in the literature for automated video game testing and the needs of video game developers in the industry. We performed a literature review on video game automated testing and applied an online survey with video game developers. The literature results show a rise in research topics related to automated video game testing. The survey results show that game developers are skeptical about using automated agents to test games. We conclude that there is a need for better testing tools that could be used easily by smaller companies with less up-front costs and researchers should focus on the testing objective, testing oracle, and offer the replication package.

show abstract

“…(1) The explorer focuses on game space exploration, using a curiosity-based reward function which takes the screenshot as input. (2) The object detector focuses on key object detection and then the investigator takes human-like behaviors to interact with detected key objects. To reduce the cost of human labeling, we adopt a few-shot object detection method to effectively detect key objects based on a small number of labeled screenshots.…”

Section: Introductionmentioning

confidence: 99%

Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation

Liu¹,

Cai²,

Zhao³

et al. 2022

Preprint

View full text Add to dashboard Cite

Deep reinforcement learning (DRL) has attracted much attention in automated game testing. Early attempts rely on game internal information for game space exploration, thus requiring deep integration with games, which is inconvenient for practical applications. In this work, we propose using only screenshots/pixels as input for automated game testing and build a general game testing agent, Inspector, that can be easily applied to different games without deep integration with games. In addition to covering all game space for testing, our agent also tries to take human-like behaviors to interact with key objects in a game, since some bugs usually happen in playerobject interactions. Inspector is based on purely pixel inputs and comprises three key modules: game space explorer, key object detector, and human-like object investigator. Game space explorer aims to explore the whole game space by using a curiosity-based reward function with pixel inputs. Key object detector aims to detect key objects in a game, based on a small number of labeled screenshots. Human-like object investigator aims to mimic human behaviors for investigating key objects via imitation learning. We conduct experiments on two popular video games: Shooter Game and Action RPG Game 1 . Experiment results demonstrate the effectiveness of Inspector in exploring game space, detecting key objects, and investigating objects. Moreover, Inspector successfully discovers two potential bugs in those two games. The demo video of Inspector is available at https: //github.com/Inspector-GameTesting/Inspector-GameTesting.

show abstract

A Survey of Video Game Testing

Cited by 39 publications

References 25 publications

Mastering uncertainty: A predictive processing account of enjoying uncertain success in video game play

Mastering uncertainty: A predictive processing account of enjoying uncertain success in video game play

Towards Automated Video Game Testing: Still a Long Way to Go

Inspector: Pixel-Based Automated Game Testing via Exploration, Detection, and Investigation

Contact Info

Product

Resources

About