BiFuzz: A Two-Stage Fuzzing Tool for Open-World Video Games

TL;DR

BiFuzz tackles automated testing challenges in open-world games by focusing on character stuck issues that arise from vast state spaces. The method employs a two-stage fuzzing workflow—Global Fuzzing to select the visiting order of keypoints and Local Fuzzing to insert waypoints—implemented as a Unity component that records reproducible traces. In a Unity-based Star Collection scenario, two play styles uncovered complementary CSIs, with PS-A detecting more issues and scenes than PS-B, highlighting the value of multi-style fuzzing for broader exploration. This approach offers a training-data-free testing alternative that can adapt to frequent game changes and reduce manual testing effort.

Abstract

Open-world video games present a broader search space than other video games, posing challenges for test automation. Fuzzing, which generates new inputs by mutating an initial input, is commonly used to uncover issues. In this study, we proposed BiFuzz, a two-stage fuzzer designed for automated testing of open-world video games, and investigated its effectiveness. The results revealed that BiFuzz mutated the overall strategy of gameplay and test cases, including actual movement paths, step by step. Consequently, BiFuzz can detect character stuck issues. The tool and its video are at https://github.com/Yusaku-Kato/BiFuzz and https://www.youtube.com/watch?v=VOrHfnLJSbk.

Figures (4)

• Figure 1: An overview of the fuzzing process in BiFuzz
• Figure 2: Strategy determination using parameters
• Figure 3: Degree of freedom determination using parameters
• Figure 4: Number of detected issues