FCEVAL: An effective and quantitative platform for evaluating fuzzer combinations fairly and easily-Reference-Cited by-同舟云学术

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FCEVAL: An effective and quantitative platform for evaluating fuzzer combinations fairly and easily

Published:2023-09 Issue: Volume:132 Page:103354
ISSN:0167-4048
Container-title:Computers & Security
language:en
Short-container-title:Computers & Security

Author:

Zhao Xiaoyun,Yang Chao,Jia Zhizhuang,Wang Yue,Ma Jianfeng

Funder

Natural Science Basic Research Program of Shaanxi Province

National Natural Science Foundation of China

Higher Education Discipline Innovation Project

Key Research and Development Projects of Shaanxi Province

Publisher

Elsevier BV

Subject

Law,General Computer Science

Reference66 articles.

1. ACM SIGPLAN, 2018. Empirical evaluation guidelines. http://www.sigplan.org/Resources/EmpiricalEvaluation/. [Online; accessed 2022-10-22].

2. Ijon: exploring deep state spaces via fuzzing;Aschermann,2020

3. Comparing fuzzers on a level playing field with fuzzbench;Asprone,2022

4. Efficient greybox fuzzing to detect memory errors;Ba,2022

5. Coverage-based greybox fuzzing as markov chain;Böhme,2016

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1. Forward-porting and its limitations in fuzzer evaluation;Information Sciences;2024-03

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