Characterizing the Quality Profile of AI-Generated C++ in Production
The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off, revealing persistent challenges with code quality and maintainability. Industry leaders, including frontier AI labs, echo these concerns. As large language models are increasingly relied upon to author production code, understanding their impact on shipped software quality has become a critical priority. However, assessing these effects in industrial workflows remains difficult due to observability barriers. We study the impact of AI-generated code on production quality within a large enterprise operating global products relied upon by bill...
| Authors | Michael Tran, Fred Lewis, Kun Yang et al. |
|---|---|
| Primary category | cs.SE |
| Published | 6 August 2026 |
| Last updated at source | 6 August 2026 |
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