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Clone-Slicer: Detecting Domain Specific Binary Code Clones through Program Slicing

In this paper, we presented a novel framework, Clone-Slicer, a domain-specific code clone detector for binary executables, that integrates program slicing and a deep learning based binary code clone modeling framework to improve the number of code clone detected. In particular, we chose pointer analysis for memory safety as our example domain to demonstrate the usefulness of our approach. We evaluated our approach using real-world applications from SPEC 2006 benchmark suite. Our results show Clone-Slicer is able to detect up to 43.64% code clones compared to prior work and further cut the time-to-solution (the time spent to verify memory bound safety) for Clone-Slicer by 32.96% compared to Clone-Hunter. As future work, we plan to apply Clone-Slicer to different domains and tasks, such as vulnerable program path discovery, and further improve the capability for code clone detection through advanced clustering algorithms. We will also study the cost-benefit tradeoffs of using such advanced algorithms.