How effective are they? Exploring large language model based fuzz driver generation
Fuzz drivers are essential for library API fuzzing. However, automatically generating fuzz drivers is a complex task, as it demands the creation of high-quality, correct, and robust API usage code. An LLM-based (Large Language Model) approach for generating fuzz drivers is a promising area of resear...
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| Main Authors: | , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2024
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/9508 https://ink.library.smu.edu.sg/context/sis_research/article/10508/viewcontent/How_Effective_Are_They__Exploring_Large_Language_Model_Based_Fuzz_Driver_Generation.pdf |
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| Institution: | Singapore Management University |
| Language: | English |