Оцінка якості коду в епоху генеративного штучного інтелекту

Abstract

The rapid integration of generative artificial intelligence into software development has significantly altered traditional coding workflows. However, the use of automated tools alone does not guarantee high code quality, nor can it completely replace human-driven architectural oversight. One promising approach to enhancing code maintenance is the balanced application of large language models for routine documentation. This technology enables an accelerated environment where teams automatically generate commit descriptions and docstrings. Yet, ensuring true quality requires a human-in-the loop approach to mitigate contextual errors, proving that while AI simplifies technical routines, it cannot substitute the developer's contextual understanding.