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SPINFER: Inferring Semantic Patches for the Linux Kernel

Abstract : In a large software system such as the Linux kernel, there is a continual need for large-scale changes across many source files, triggered by new needs or refined design decisions. In this paper, we propose to ease such changes by suggesting transformation rules to developers, inferred automatically from a collection of examples. Our approach can help automate large-scale changes as well as help understand existing large-scale changes, by highlighting the various cases that the developer who performed the changes has taken into account. We have implemented our approach as a tool, Spinfer. We evaluate Spinfer on a range of challenging large-scale changes from the Linux kernel and obtain rules that achieve 86% precision and 69% recall on average.
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Submitted on : Sunday, July 26, 2020 - 10:40:47 AM
Last modification on : Tuesday, October 25, 2022 - 4:21:09 PM
Long-term archiving on: : Tuesday, December 1, 2020 - 7:02:24 AM


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  • HAL Id : hal-02906912, version 1


Lucas Serrano, Van-Anh Nguyen, Ferdian Thung, Lingxiao Jiang, David Lo, et al.. SPINFER: Inferring Semantic Patches for the Linux Kernel. USENIX Annual Technical Conference, Jul 2020, Boston / Virtual, United States. ⟨hal-02906912⟩



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