Real World Code
Real-world code research focuses on bridging the gap between large language models (LLMs) and practical software development, aiming to improve the quality, security, and efficiency of automatically generated code. Current research emphasizes developing methods for generating equivalent code representations, ensuring code correctness through techniques like hierarchical debugging and polyhedral modeling, and mitigating security vulnerabilities via prompt optimization and generative adversarial networks. This field is significant because it directly impacts software engineering practices, potentially increasing developer productivity and improving software reliability and security.
Papers
Gui at MixMT 2022 : English-Hinglish: An MT approach for translation of code mixed data
Akshat Gahoi, Jayant Duneja, Anshul Padhi, Shivam Mangale, Saransh Rajput, Tanvi Kamble, Dipti Misra Sharma, Vasudeva Varma
Navigating the challenges in creating complex data systems: a development philosophy
Sören Dittmer, Michael Roberts, Julian Gilbey, Ander Biguri, AIX-COVNET Collaboration, Jacobus Preller, James H. F. Rudd, John A. D. Aston, Carola-Bibiane Schönlieb