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The analysis of software similarity has many applications such as detecting code clones, software plagiarism, code theft, and polymorphic malware. Because often source code is unavailable and code obfuscation is used to avoid detection, there has been much research on developing effective models to capture runtime behavior to aid detection. Existing models focus on low-level information such as dependency or purely occurrence of function calls, and suffer from poor precision, poor scalability, or both. To overcome limitations of existing models, this paper introduces a precise and succinct behavior representation that characterizes high-level object-accessing patterns as regular expressions.
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