Write a Blog >>
ICST 2022
Mon 4 - Fri 8 April 2022
Wed 6 Apr 2022 15:45 - 16:00 at Margaret Hamilton - ICST AI II Chair(s): Donghwan Shin

As it is the case with any very complex and interactive software, many video games are released with various minor or major issues that can potentially affect the user experience, cause security issues for players, or exploit the companies that deliver the products. In order to test their games, companies invest important resources in quality assurance personnel who usually perform the testing mostly manually. The main goal of our work is to automate various parts of the testing process that involve human users (testers) and thus to reduce costs and run more tests in less time. The secondary goal is to provide mechanisms to make test specification writing easier and more efficient. We focus on solving initial real-world problems that have emerged from several discussions with industry partners. In this paper, we present RiverGame, a tool that allows game developers to automatically test their products from different points of view: the rendered output, the sound played by the game, the animation and movement of the entities, the performance or various statistical analyses. We also address the problem of input priorities, scheduling, and directing the testing effort towards custom and dynamic directions. At the core of our methods, we use state-of-the-art artificial intelligence methods for analysis and a behavior-driven development methodology for test specifications. Our technical solution is open-source, independent of game engine, platform, and programming language.

Wed 6 Apr

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

15:15 - 16:30
ICST AI IITesting Tools / Research Papers / Industry at Margaret Hamilton
Chair(s): Donghwan Shin University of Luxembourg
Learning Realistic Mutations: Bug Creation for Neural Bug Detectors
Research Papers
Cedric Richter Carl von Ossietzky Universität Oldenburg / University of Oldenburg, Heike Wehrheim Carl von Ossietzky Universität Oldenburg / University of Oldenburg
SUPERNOVA: Automating Test Selection and Defect Prevention in AAA Video Games Using Risk Based Testing and Machine Learning
Alexander Senchenko Electronics Arts, Naomi Patterson Electronics Arts, Hamman Samuel Electronics Arts, Dan Ispir Electronics Arts
RiverGame - a game testing tool using artificial intelligence
Testing Tools
Ciprian Paduraru University of Bucharest, Miruna Gabriela Paduraru University of Bucharest , Alin Stefanescu University of Bucharest
Machine Learning Based Invariant Generation: A Framework and Reproducibility Study
Research Papers
Jan Haltermann University of Oldenburg, Heike Wehrheim Carl von Ossietzky Universität Oldenburg / University of Oldenburg
Live Q&A
Discussion and Q&A
Research Papers