Synthetic Data Augmentation Enhances DeepSeek Coder Robustness Against Adversarial Code Perturbations

This report synthesises findings from 12 peer-reviewed papers addressing the following research question: What is the impact of synthetic data augmentation on the robustness of DeepSeek Coder against adversarial code perturbations as measured by accuracy degradation on the MBPP dataset. 7 claims were extracted from source literature; 7 were independently verified against retrieved documents. An automated multi-reviewer quality assessment produced a score of 8.7/10. This report is a machine-generated literature synthesis and does not constitute original research.

Research goal: What is the impact of synthetic data augmentation on the robustness of DeepSeek Coder against adversarial code perturbations as measured by accuracy degradation on the MBPP dataset?

Autonomous literature synthesis. Automated review score: 8.7/10. Full text and citation available at Assignee Research.