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Work in progress: Unlocking code generation through synergistic prompt engineering
Date Issued
2025
Publisher
IEEE
ISBN
9798331542788
9798331542795
Citation
Ho, K. H., Georgiades, M., Fan, T. K. J., Hou, Y., Fong, K. C. K., & Chan, T. T. (2025). Work in progress: Unlocking code generation through synergistic prompt engineering. In Brito, C. D. R., & Ciampi, M. M. (Eds.). 2025 IEEE Engineering education world conference (EDUNINE). 2025 IEEE Engineering Education World Conference (EDUNINE), Montevideo, Uruguay. IEEE.
Type
Conference Paper
Abstract
Prompt engineering is crucial for optimizing large language models in code generation. This paper explores a synergistic prompt engineering approach that integrates complementary prompting techniques for solving programming problems. Preliminary experiments show that by leveraging the strengths of various prompting techniques, our synergistic approach significantly outperforms traditional single- prompting techniques, improving the accuracy of code generation for Python and C++ exercises. These findings suggest that our synergistic approach is a valuable tool for students, enhancing their interactions with large language models and improving AI-driven programming education.
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