Unveiling Memorization in Code Models
Zhou Yang, Zhipeng Zhao, Chenyu Wang, Jieke Shi, Dongsun Kim, DongGyun Han, David Lo
Abstract
The availability of large-scale datasets, advanced architectures, and powerful computational resources have led to effective code models that automate diverse software engineering activities. The datasets usually consist of billions of lines of code from both open-source and private repositories. A code model memorizes and produces source code verbatim, which potentially contains vulnerabilities, sensitive information, or code with strict licenses, leading to potential security and privacy issues.
Topics & Concepts
Computer scienceCode (set theory)MemorizationProgramming languageLinguisticsPhilosophySet (abstract data type)Software Engineering ResearchSoftware Testing and Debugging TechniquesTopic Modeling