Autograding of Programs Using Siamese Network-Based Semantic Code Similarity Detection
The proposed Siamese Network-based Code Similarity Detection (SNCSD) approach computes contextual embeddings to capture both syntactic and semantic similarities between student-submitted code and reference solutions to offer a more accurate, transparent, and scalable alternative to traditional grading approaches.