Artificial intelligence (AI) coding assistants, such as GitHub Copilot, are gaining popularity for their purported ability to enhance programmer efficiency. However, recent studies cast doubt on their overall impact on code quality.
A comprehensive report by GitClear analyzed over 200 million lines of code and revealed a concerning decline in code reuse in 2023. Code reuse is a widely adopted practice to minimize redundant system development. This finding suggests that AI coding assistants may be hindering the adoption of this fundamental software engineering principle.
Further research by Harness and Google has yielded mixed results. Harness observed an increase in debugging time and security vulnerabilities when using AI-generated code compared to code written by humans. On the other hand, Google reported that AI can accelerate code reviews and enhance documentation, but may compromise software stability.
These findings highlight the need for a balanced approach when employing AI coding assistants. While they can potentially streamline certain coding tasks, it is crucial to consider their potential drawbacks on overall code quality and stability. Developers should carefully evaluate the benefits and limitations of these tools before incorporating them into their workflows.
Original source: Read the full article on TechCrunch
