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AI‑Assisted Software Development describes practices and tools that integrate machine learning into coding, testing, code review and development workflows to boost productivity and automate routine tasks. The focus is human–AI collaboration, governance and quality assurance, plus managing risks such as bias and security.
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AI-assisted software development uses models to analyze, create, explain, and test source code and to support engineering decisions.
The approach grew from combining machine learning with program analysis and software tools; projects such as Microsoft’s CodeBERT show pretrained models for natural language and source code.
A developer works with a fast assistant that suggests code and prepares checks, while the developer remains responsible for review.
AI augments development with context-aware suggestions and analysis.
Typical tasks include completion, refactoring, tests, and documentation.
Review, tests, privacy, and license checks remain part of development.
AI assistance can speed up feedback and routine work when teams verify suggestions thoughtfully.
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