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- W3205213881 abstract "Detecting code flaws in programs is a vital aspect of software maintenance and security. Classic code flaw detection techniques rely on program analysis to check whether the code logic violates certain pre-define rules. In many cases, however, program analysis falls short of understanding the semantics of a function (e.g., the functionality of an API), and thus is difficult to judge whether the function and its related behaviors would lead to a security bug. In response, we propose an automated data-driven annotation strategy to enhance the understanding of the semantics of functions during flaw detection. Our designed SparrowHawk source code analysis system utilizes a programming language aware text similarity comparison to efficiently annotate the attributes of functions. With the annotation results, SparrowHawk makes use of the Clang static analyzer to guide security analyses." @default.
- W3205213881 created "2021-10-25" @default.
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- W3205213881 date "2021-01-01" @default.
- W3205213881 modified "2023-10-16" @default.
- W3205213881 title "SparrowHawk: Memory Safety Flaw Detection via Data-Driven Source Code Annotation" @default.
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- W3205213881 doi "https://doi.org/10.1007/978-3-030-88323-2_7" @default.
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