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Book Open access Oct 2026

Hybrid Fuzzing in Input Generation Logic

The core challenge of fuzzing is to consistently generate test inputs that are both syntactically valid and semantically diverse. However, mutation-based coverage-guided fuzzing often struggles to achieve this, especially for highly structured formats. Two lines of work have emerged to address this challenge: (1) hybri...

Si-Wei Wei, Shi-Hao Zhu, Rui-Jie Meng et al. · 1 citation
Open access Oct 2026

Fixed-Point Guided ADS Scenario Generation via Multi-modal LLM Reasoning and Software Testing

Robust scenario generation is essential for systematically testing Autonomous Driving Systems (ADSs) under rare and safety-critical conditions. However, search-based approaches often lack semantic guidance, whereas specification-based approaches rely heavily on manually constructed rules. Existing LLM-assisted techniqu...

Xu-Dong Zhang, Shi-Hao Zhu, Yan Cai · 0 citations

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