AI-Assisted Software Development
Overview
AI-assisted software development studies how language models and coding agents can support work from requirements and design through implementation, testing, review, and maintenance. Common approaches include IDE code completion and chat, repository-aware retrieval, multi-step agents, and specification-driven workflows that use plans, tests, and architectural constraints to guide changes. Evaluation spans coding benchmarks and repository-level issue fixing, as well as real IDE traces, pull requests, static analysis, security checks, and fuzz testing. A central tension is that AI can speed up routine work while creating new costs in verification, security, maintainability, and developer understanding, so reliable use depends on effective feedback and human oversight.
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