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In this study, we conducted experiments to validate the effectiveness of the proposed method.
The experiment was carried out in the process of converting SECS messages written by developers into XML code, where completed XML example code was pre-stored in a database. Based on this, a prompt template was designed to account for considerations when automatically converting SECS messages into XML code.
The system operates as follows:
First, when the user inputs a sentence requesting code generation, relevant information is retrieved from the stored database. Then, the system proceeds by using the configured prompt template and generative AI to generate the requested code.
As mentioned earlier, the similarity of the results was evaluated using the ROUGE-1, ROUGE-2, and ROUGE-L metrics.
Based on the predefined evaluation criteria, the experimental results demonstrated a high level of similarity, confirming the effectiveness of the proposed method.
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IEEE/ICACT20250028 Slide.21
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