Towards Systematic and Dynamic Task Allocation for Collaborative Parallel Fuzzing

Pham, Van-Thuan; Nguyen, Manh-Dung; Ta, Quang-Trung; Murray, Toby; Rubinstein, Benjamin I. P.

doi:10.1109/ase51524.2021.9678810

Cited by 6 publications

(1 citation statement)

References 19 publications

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“…From the scripts provided by AFLGo, we selected four projects using CI as experimental projects: jasper, libming, libxml2 and lrzip. These widespread open-source projects are often used in related research [19,26,27] and have a certain degree of representativeness, which can reduce external validity threats to a certain extent. However, we cannot ensure that the proposed method will have the same effectiveness on other projects.…”

Section: Threates To Validitymentioning

confidence: 99%

CIDFuzz: Fuzz testing for continuous integration

et al. 2023

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As agile software development and extreme programing have become increasingly popular, continuous integration (CI) has become a widely used collaborative work method. However, it is common to make changes frequently to a project during CI. If existing testing methods are applied to CI directly, it will be difficult to make testing resources focus on changes generated by CI, which results in insufficient testing for changes. To solve this problem, we propose a fuzz testing method for CI. First, differential analysis is performed to determine the change points generated during CI, change points are added to the taint source set, and static analysis is conducted to calculate the distances between each basic block and the taint sources. Then, the project under test is instrumented according to the distances. During fuzz testing, testing resources are allocated based on seed coverage to test the change points effectively. Using the proposed methods, we implement CIDFuzz as a prototype tool, and experiments are conducted on four open-source projects that use CI. Experimental results show that, compared with AFL and AFLGo, CIDFuzz can reduce the time costs of covering change points up to 39.59% and 41.64%, respectively. Also, CIDFuzz can reduce the time costs of reproducing vulnerabilities up to 34.78% and 25.55%.

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Section: Threates To Validitymentioning

confidence: 99%