Research Raises Concerns Over AI Impact on Code Quality

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Recent findings from GitClear, a developer analytics firm, indicate that the increasing reliance on AI assistance in software development may be adversely affecting code quality. The study, which analyzed a staggering 150 million changed lines of code from both private and open-source projects, has brought to light several concerning trends, including a rise in code churn and a higher incidence of repetitive code.

GitHub’s Copilot, a leading AI coding assistant used by over a million developers, has been reported to increase task completion speed by 55%, with 46% of code in enabled files being generated by the tool. However, GitClear’s research shifts the focus from the quantity to the quality of code produced with AI assistance. The study points out that AI tools tend to suggest additions to the code but seldom recommend updates, relocations, or deletions. This pattern raises questions about the conciseness and readability of the resulting code.

A significant finding of the research is the increase in code churn, which has escalated to 7.1% from 3.3% in 2020. Additionally, there has been a noted decrease in the movement of code, suggesting a reduction in code refactoring activities. The researchers have expressed concerns over the growing tendency to use copied and pasted code, citing it as a major challenge for the long-term maintainability of software.

While the exact reasons behind these trends are subject to speculation, the researchers associate them with the burgeoning use of AI in coding. They advise engineering leaders to closely monitor these trends and consider their potential impact on future product maintenance.

The study concludes that AI coding assistants, in their current state, are unlikely to replace human developers. The AI tools are deemed too error-prone and not yet capable of securely modifying existing code. This insight may offer some reassurance to developers who fear being supplanted by AI, highlighting the current limitations and challenges of AI in coding scenarios.

Sources Include: The Register

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