Finding and repairing problems in code is a time-consuming and frequently unpleasant element of software engineers’ day-to-day work. Can deep learning solve this challenge and help engineers offer better software faster? In a new study, Self-Supervised Bug Detection and Repair, presented at the 2021 Conference on Neural Information Processing Systems (NeurIPS 2021), a promising deep learning model was proposed called BugLab. BugLab can be trained to find and repair flaws without the need for labeled data by playing a “hide and seek” game.
Finding and fixing flaws in code necessitates not just thinking about the structure of the code but also interpreting confusing natural language cues left by software engineers in code comments, variable names, and other places. For example, the code snippet below resolves an issue in a GitHub open-source project.
Disclaimer: BugLab doesn’t use GPT-3
Source: https://www.marktechpost.com/2021/12/17/microsoft-research-introduces-buglab-a-deep-learning-model-to-detect-and-fix-bugs-without-using-labelled-data/