Self-Collaboration Code Generation via ChatGPT
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Abstract
Although large language models (LLMs) have demonstrated remarkable code-generation ability, they still struggle with complex tasks. In real-world software development, humans usually tackle complex tasks through collaborative teamwork, a strategy that significantly controls development complexity and enhances software quality. Inspired by this, we present a self-collaboration framework for code generation employing LLMs, exemplified by ChatGPT. Specifically, through role instructions, (1) Multiple LLM agents act as distinct “experts,” each responsible for a specific subtask within a complex task; (2) Specify the way to collaborate and interact, so that different roles form a virtual team to facilitate each…
Citation impact
175
total citations
- FWCI
- 53.42
- Percentile
- 100%
- References
- 23
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Authors
4Topics & keywords
Keywords
- Computer science
- Code generation
- Code (set theory)
- Software engineering
- Programming language
- Computer security
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