Memory-related vulnerabilities constitute severe threats to the security of modern software.
Despite the success of deep learning-based approaches to generic vulnerability detection …

This paper introduces an innovative approach that combines Large Language Models
(LLMs) with Formal Verification strategies for automatic software vulnerability repair. Initially …

Machine learning and its promising branch deep learning have shown success in a wide
range of application domains. Recently, much effort has been expended on applying deep …

This paper presents SVF, a tool that enables scalable and precise interprocedural Static
Value-Flow analysis for C programs by leveraging recent advances in sparse analysis. SVF …

Code retrieval techniques and tools have been playing a key role in facilitating software
developers to retrieve existing code fragments from available open-source repositories …

Attack surface reduction through the removal of unnecessary application features and code
is a promising technique for improving security without incurring any additional overhead …

Machine learning and its promising branch deep learning have proven to be effective in a
wide range of application domains. Recently, several efforts have shown success in …

Understanding program behaviors is important to verify program properties or to optimize
programs. Static analysis is a widely used technique to approximate program behaviors via …

When dealing with millions of lines of code, we still cannot have the cake and eat it: sparse
value-flow analysis is powerful in checking source-sink problems, but existing work cannot …

Detecting memory leak at industrial scale is still not well addressed, in spite of the
tremendous effort from both industry and academia in the past decades. Existing work …