Automated Fuzz Generators for High-Coverage Tests Based on Program Branch Predications
Jinjing Zhao, Ling Pang · 2018
Fuzzing is an approach to software testing whereby the system being tested is bombarded with test cases generated by another program. A key problem in Fuzzing test is how to efficiently reduce the fuzzing data scale while satisfying high fuzzing veracity and vulnerability coverage. In this paper, a new automated fuzz generator method named as WS-Fuzz is presented, which has high program executing path coverage with the information from the static analysis and dynamic property of the program. The evaluation shows that WS-Fuzz can use less number of iterations and testing time to achieve higher test path coverage.