Application of AI Large Language Models in the Full Software Development Lifecycle

The article explores how AI large language models (such as ChatGPT) can assist developers throughout the entire software development lifecycle.

In the requirement analysis phase, AI can extract key points from requirement documents and generate flowcharts to clarify functional requirements.

During technical solution design, AI helps devise large‑table update strategies (e.g., batch updates with backup reminders), researches industry‑standard solutions, answers detailed design questions, and translates or summarizes English documentation.

For coding, tools like GitHub Copilot generate code snippets, unit tests, documentation, and command‑line instructions from natural language comments; they also support language translation, code explanation, and de‑obfuscation of confusing code.

In testing, AI automatically creates test cases and scripts, provides performance‑testing suggestions and optimization advice, and performs security‑vulnerability analysis.

When releasing software, AI generates deployment scripts tailored to the project’s stack and helps diagnose and resolve deployment issues.

In the operations phase, AI aids in fault diagnosis, analyzes user feedback to uncover needs and pain points, and suggests improvements.

The article also highlights important cautions: model accuracy limitations, hallucinations, knowledge cutoff (September 2021), intellectual‑property uncertainties, and privacy/compliance considerations when using AI‑generated content.