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Patching Locking Bugs Statically with Crayons
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AI
DOI：10.1145/3548684.png)
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Abstract
En 中文
The Linux Kernel is a world-class operating system controlling most of our computing infrastructure: mobile devices, Internet routers and services, and most of the supercomputers. Linux is also an example of low-level software with no comprehensive regression test suite (for good reasons). The kernel's tremendous societal importance imposes strict stability and correctness requirements. Th Over the past decade, a significant progress has been made in dynamic APR. However, dynamic APR techniques do not translate naturally to systems without tests. We present a static APR technique addressing sequential locking API misuse bugs in the Linux Kernel. We attack the key challenge of static APR, namely, the lack of detailed program specification, by combining static analysis with machine learning to complement the information presented by the static analyzer. In experiments on historical real-world bugs in the kernel, we were able to automatically reproduce or propose equivalent patches in 85% of the human-made patches, and automatically rank them among the top three candidates for 64% of the cases and among the top five for 74%.
Keywords:
Automated repair
static program repair
api misuse
Journal
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IF:
6.2
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1.2K
Citations:
3.4K