Sony developers share how machine learning can improve QA
During a talk given at the recent CEDEC event in Yokohama, Japan, development leads within Sony discussed their recent efforts to implement AI and machine learning models to improve efficiency and accuracy within the QA process.
The talk was led by machine learning researchers from the company's Game Service R&D department, Hiroyuki Yabe and Yutaro Miynotauchi, alongside Nakahara Hiroki, a software engineer focused on software QA engineering. It was aimed at priming fellow creators on the ways the company had integrated AI into the QA process using real PS5 hardware, corefllecting only on-screen and audio information similar to human-driven Q&A while allowing for titles to be tested more regularly and with greater efficiency.
More regular testing in this fashion accomplished autonomously allowed teams to eliminate more bugs earlier thanks to more regular testing, as manual testing can otherwise only be conducted a few times per development cycle and a bug caught too late in development has a chance of impacting release.
For this talk, the team shared their findings using the software to automate QA operations in PlayStation 5 launch title Astro's Playroom. This was notable as one key feature requiring extensive QA testing was the integration of game progress with hardware functionality such as the PS5's Activity Cards, which could track progress on particular objectives as players made their way through a level.
When researching how to integrate the technology into the testing process, the team had a few conditions that needed to be met: any testing system must not rely on game-specific tools that would then need to be remade for use in other games – in other words, AI testing for a shooting game mustn't rely on aim assistance that can't be applied to a platformer or another shooter, and so on.
It also must be achievable at a realistic cost that makes such automation worthwhile and it must also be simple enough that even those without technical experience could create an
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