Solving the task of finding source code given its description, which could be useful for both experienced and novice programmers
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Updated
May 23, 2024 - Jupyter Notebook
Solving the task of finding source code given its description, which could be useful for both experienced and novice programmers
A research project to fine-tune a Large Language Model (LLM) to generate code from commands in Bahasa Melayu.
Domain-specific adaptation of CodeT5 for Python docstring generation. Compares pre-trained vs fine-tuned performance using NLP metrics (ROUGE, METEOR, BERTScore), showing significant improvements after targeted training.
Repository for the master's thesis: "Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing" (van der Vleuten, 2023)
A Machine Learning research project focused on automated Software Vulnerability Classification (CWE) using fine-tuned linguistic models (CodeBERT, RoBERTa, CodeT5) on the Juliet C/C++ Test Suite.
Interactive DSA Practice platform , A full-stack web app for coding practice through personal contest style tests, with real-time code execution and automated code analysis using a fine-tuned CodeT5 model + Gemini API.
Generating Vulnerability Security Fixes with Code Language Models
Knowledge distillation pipeline for training a smaller CodeT5-based model to generate test assertions. Part of a Bachelor Thesis at TU Delft focusing on efficient automated test assertion generation.
human understandable explanation for software vulnerability prediction
Code Archaeologist is an intelligent developer tool that analyzes legacy and messy codebases to uncover hidden insights — detecting dead code, measuring complexity, and generating human-readable narratives of code evolution using static analysis and NLP.
Fine-tuning CodeT5 for Python code generation on the MBPP dataset. Features custom TensorFlow training loops, mixed precision, XLA optimization, and distributed multi-GPU strategies.
Privacy-preserving code completion with AST-based obfuscation and CodeT5
Code completion on CodeSearchNet: Seq2Seq LSTM vs CodeT5 vs decoder-only Transformer, served via FastAPI
Code for "The role of positional encodings in the ARC benchmark" (arXiv:2502.00174)
AI-powered diagnostic assistant that rewrites C/C++ compiler errors into security-focused explanations using a fine-tuned CodeT5 model.
Spider Text-to-SQL data selection with CodeT5-small, iterative utility updates, and LEAD-style dynamic selection.
A machine learning-based system for automated assessment of Java code using CodeT5+ embeddings, feature fusion, and CatBoost regression to predict quality scores from 0 to 10.
AI-powered code review comment generator — a CodeT5 model fine-tuned on real GitHub PR reviews, with a fine-tuned vs. baseline ablation comparison. DLNLP mini-project.
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