Leveraging ChatGPT to Enhance Debugging: Evaluating AI-Driven Solutions in Software Development

Abstract

Debugging is a crucial component of software development, focusing on identifying and correcting problems, commonly known as bugs, in code. Recent advances in artificial intelligence (AI) have introduced new opportunities for automating this process using language models such as ChatGPT. This article explores the use of ChatGPT in addressing programming challenges, assessing its ability to detect, anticipate, and rectify errors in code. The research examines ChatGPT’s debugging capabilities by evaluating its natural language processing, knowledge representation, and pattern recognition skills. The text compares ChatGPT’s performance with conventional debugging tools through real-world examples and case studies. The findings suggest that ChatGPT can effectively assist in debugging by automatically identifying and correcting errors, predicting issues early in the development phase, and clarifying the underlying causes of bugs. However, the system’s effectiveness depends on the quality of its training data and architecture. While ChatGPT has the potential to be a valuable tool in the debugging process, it is essential to combine it with traditional debugging methods to ensure accuracy and reliability. Further research is needed to enhance ChatGPT’s capabilities and evaluate its effectiveness in real-world scenarios.