Sushanth Chilla

College of Engineering

2023 article

SANN: Programming Code Representation Using Attention Neural Network with Optimized Subtree Extraction

PROCEEDINGS OF THE 32ND ACM INTERNATIONAL CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, CIKM 2023, pp. 783–792.

By: M. Hoq n, S. Chilla n, M. Ranjbar n, P. Brusilovsky* & B. Akram n

author keywords: program analysis; code representation; static analysis; algorithm detection; program correctness prediction
TL;DR: The results indicate the effectiveness of the SANN model in capturing important syntactic and semantic information from students' code, allowing the construction of accurate student models, which serve as the foundation for generating adaptive instructional support such as individualized hints and feedback. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science; OpenAlex)
Sources: Web Of Science, ORCID, NC State University Libraries
Added: March 25, 2024

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