Grammar-aware test case trimming for efficient hybrid fuzzing

Author:

Zhao YiruORCID,Gao Long,Wan Qihan,Zhao Lei

Funder

National Natural Science Foundation of China

Guangxi Key Research and Development Program

Publisher

Elsevier BV

Reference32 articles.

1. Afl-tmin;afl-tmin,2013

2. Effective and scalable black-box fuzzing approach for modern web applications;Alsaedi;J. King Saud Univ. Comput. Inf. Sci.,2022

3. SCIPOG: Seeding and constraint support in IPOG strategy for combinatorial t-way testing to generate optimum test cases;Aminu Muazu;J. King Saud Univ. Comput. Inf. Sci.,2023

4. BOOMPizer: Minimization and prioritization of CONCOLIC based boosted MC/DC test cases;Barisal;J. King Saud Univ. Comput. Inf. Sci.,2022

5. Chen, Y., Ahmadi, M., Wang, B., Lu, L., et al., 2020. {MEUZZ}: Smart Seed Scheduling for Hybrid Fuzzing. In: 23rd International Symposium on Research in Attacks, Intrusions and Defenses. RAID 2020, pp. 77–92.

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