Catch Silent Regressions for $0: A Behavior-Diff Loop for AI-Assisted PRs

说明与用途

在合并 PR 之前添加零成本行为差异循环，以捕获隐藏的回归，使用 MonkeyCode 的免费 AI 模型和临时服务器。

问题

AI‑generated code can silently change behavior; green tests may still pass while user‑facing contracts shift, leading to regressions that surface weeks later.

结果

The workflow adds a cheap, repeatable behavior comparison that catches silent regressions before they become incidents, without extra cost.

工作流

• 1. Capture a behavioral snapshot: select affected functions/endpoints and create a JSON file of edge‑case inputs.
• 2. Ask a free AI model (MonkeyCode) to generate a diff‑runner script that runs both old and new implementations with the same inputs.
• 3. Provision a free disposable server, copy old/new code, the generated script, and the cases file, then execute the script.
• 4. Review diff output; if any unexpected differences exist, treat them as regressions and fail the CI gate. If all OK, merge the PR.

证据

Traditional tests assert what you remembered to write. AI-generated code often changes behavior in ways no one remembers to check.

来源

The loop has four stages: snapshot, generate, execute, compare. You can run it entirely on a free server, using free model quotas for the creative part.

来源