Pre Trained Code Model

Pre-trained code models leverage large code datasets to learn representations of code, enabling improved performance on various downstream tasks like code generation, bug detection, and code search. Current research emphasizes improving data quality for pre-training, exploring different model architectures (including Transformer-based models and those incorporating graph neural networks), and investigating efficient fine-tuning strategies such as prompt tuning to reduce computational costs. These advancements are significantly impacting software engineering by automating tasks, improving code quality, and accelerating software development.