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Code generation tools are essential to help developers in the softwaredevelopment process. Existing tools often disconnect with the working context,i.e., the code repository, causing the generated code to be not similar tohuman developers. In this paper, we propose a novel code generation framework,dubbed \textbf{$A^3$}-CodGen, to harness information within the code repositoryto generate code with fewer logical errors, code redundancy, andlibrary-related compatibility issues. We identify three categories ofrepresentative information for the code repository: local-aware informationfrom current code file, global-aware information from other code files, andthird-party-library information. Results demonstrate that by adopting the\textbf{$A^3$}-CodGen framework, we successfully extract, fuse, and feed coderepository information into the LLM, generating more accurate, efficient, andhighly reusable code. The effectiveness of our framework is further underscoredby generating code with a higher reuse rate, compared to human developers. Thisresearch contributes significantly to the field of code generation, providingdevelopers with a more powerful tool to address the evolving demands insoftware development in practice.

Context-Aware Code Generation Framework for Code Repositories: Local, Global, and Third-Party Library Awareness