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ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

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name ai-regression-testing description Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change. metadata {"origin":"ECC"} AI Regression Testing Testing patterns specifically designed for AI-assisted development, where the same model writes code and reviews it — creating systematic blind spots that only automated tests can catch. When to Activate AI agent (Claude Code, Cursor, Codex) has modified API routes or backend logic A bug was found and fixed — need to prevent re-introduction Project has a sandbox/mock mode that can be leveraged for DB-free testing Running /bug-check or similar review commands after code changes Multiple code paths exist (sandbox vs production, feature flags, etc.) The Core Problem When an AI writes code and then reviews its own work, it carries the same assumptions into both steps. This creates a predictable failure pattern: AI writes fix → AI reviews fix → AI says "looks correct" → Bug still exists Real-world example (observed in production): Fix 1: Added notification_settings to API response → Forgot to add it to the SELECT query → AI reviewed and missed it (same blind spot) Fix 2: Added it to SELECT query → TypeScript build error (column not in generated types) → AI reviewed Fix 1 but didn't catch the SELECT issue Fix 3: Changed to SELECT * → Fixed production path, forgot sandbox path → AI reviewed and missed it AGAIN (4th occurrence) Fix 4: Test caught it instantly on first run PASS: The pattern: sandbox/production path inconsistency is the #1 AI-introduced regression. Sandbox-Mode API Testing Most projects with AI-friendly architecture have a sandbox/mock mode. This is the key to fast, DB-free API testing. Setup (Vitest + Next.js App Router) // vitest.config.ts import { defineConfig } from "vitest/config" ; import path from "path" ; export default defineConfig ({ test : { environment : "node" , globals : true , include : [ "__tests__/**/*.test.ts" ], setupFiles : [ "__tests__/setup.ts" ], }, resolve : { alias : { "@" : path. resolve (__dirname, "." ), }, }, }); // __tests__/setup.ts // Force sandbox mode — no database needed process. env . SANDBOX_MODE = "true" ; process. env . NEXT_PUBLIC_SUPABASE_URL = "" ; process. env . NEXT_PUBLIC_SUPABASE_ANON_KEY = "" ; Test Helper for Next.js API Routes // __tests__/helpers.ts import { NextRequest } from "next/server" ; export function createTestRequest ( url : string , options ?: { method?: string ; body?: Record< string , unknown >; headers?: Record< string , string >; sandboxUserId?: string ; }, ): NextRequest { const { method = "GET" , body, headers = {}, sandboxUserId } = options || {}; const fullUrl = url. startsWith ( "http" ) ? url : `http://localhost:3000 ${url} ` ; const reqHeaders : Record < string , string > = { ...headers }; if (sandboxUserId) { reqHeaders[ "x-sandbox-user-id" ] = sandboxUserId; } const init : { method : string ; headers : Record < string , string >; body ?: string } = { method, headers : reqHeaders, }; if (body) { init. body = JSON . stringify (body); reqHeaders[ "content-type" ] = "application/json" ; } return new NextRequest (fullUrl, init); } export async function parseResponse ( response : Response ) { const json = await response. json (); return { status : response. status , json }; } Writing Regression Tests The key principle: write tests for bugs that were found, not for code that works . // __tests__/api/user/profile.test.ts import { describe, it, expect } from "vitest" ; import { createTestRequest, parseResponse } from "../../helpers" ; import { GET , PATCH } from "@/app/api/user/profile/route" ; // Define the contract — what fields MUST be in the response const REQUIRED_FIELDS = [ "id" , "email" , "full_name" , "phone" , "role" , "created_at" , "avatar_url" , "notification_settings" , // ← Added after bug found it missing ]; describe ( "GET /api/user/profile" , () => { it ( "returns all required fields" , async () => { const req = createTestRequest ( "/api/user/profile" ); const res = await GET (req); const { status, json } = await parseResponse (res); expect (status). toBe ( 200 ); for ( const field of REQUIRED_FIELDS ) { expect (json. data ). toHaveProperty (field); } }); // Regression test — this exact bug was introduced by AI 4 times it ( "notification_settings is not undefined (BUG-R1 regression)" , async () => { const req = createTestRequest ( "/api/user/profile" ); const res = await GET (req); const { json } = await parseResponse (res); expect ( "notification_settings" in json. data ). toBe ( true ); const ns = json. data . notification_settings ; expect (ns === null || typeof ns === "object" ). toBe ( true ); }); }); Testing Sandbox/Production Parity The most common AI regression: fixing production path but forgetting sandbox path (or vice versa). // Test that sandbox responses match the expected contract describe ( "GET /api/user/messages (conversation list)" , () => { it ( "includes partner_name in sandbox mode" , async () => { const req = createTestRequest ( "/api/user/messages" , { sandboxUserId : "user-001" , }); const res = await GET (req); const { json } = await parseResponse (res); // This caught a bug where partner_name was added // to production path but not sandbox path if (json. data . length > 0 ) { for ( const conv of json. data ) { expect ( "partner_name" in conv). toBe ( true ); } } }); }); Integrating Tests into Bug-Check Workflow Custom Command Definition <!-- .claude/commands/bug-check.md --> # Bug Check ## Step 1: Automated Tests (mandatory, cannot skip) Run these commands FIRST before any code review: npm run test # Vitest test suite npm run build # TypeScript type check + build - If tests fail → report as highest priority bug - If build fails → report type errors as highest priority - Only proceed to Step 2 if both pass ## Step 2: Code Review (AI review) 1. Sandbox / production path consistency 2. API response shape matches frontend expectations 3. SELECT clause completeness 4. Error handling with rollback 5. Optimistic update race conditions ## Step 3: For each bug fixed, propose a regression test The Workflow User: "バグチェックして" (or "/bug-check") │ ├─ Step 1: npm run test │ ├─ FAIL → Bug found mechanically (no AI judgment needed) │ └─ PASS → Continue │ ├─ Step 2: npm run build │ ├─ FAIL → Type error found mechanically │ └─ PASS → Continue │ ├─ Step 3: AI code review (with known blind spots in mind) │ └─ Findings reported │ └─ Step 4: For each fix, write a regression test └─ Next bug-check catches if fix breaks Common AI Regression Patterns Pattern 1: Sandbox/Production Path Mismatch Frequency : Most common (observed in 3 out of 4 regressions) // FAIL: AI adds field to production path only if ( isSandboxMode ()) { return { data : { id, email, name } }; // Missing new field } // Production path return { data : { id, email, name, notification_settings } }; // PASS: Both paths must return the same shape if ( isSandboxMode ()) { return { data : { id, email, name, notification_settings : null } }; } return { data : { id, email, name, notification_settings } }; Test to catch it : it ( "sandbox and production return same fields" , async () => { // In test env, sandbox mode is forced ON const res = await GET ( createTestRequest ( "/api/user/profile" )); const { json } = await parseResponse (res); for ( const field of REQUIRED_FIELDS ) { expect (json. data ). toHaveProperty (field); } }); Pattern 2: SELECT Clause Omission Frequency : Common with Supabase/Prisma when adding new columns // FAIL: New column added to response but not to SELECT const { data } = await supabase . from ( "users" ) . select ( "id, email, name" ) // notification_settings not here . single (); return { data : { ...data, notification_settings : data. notification_settings } }; // → notification_settings is always undefined // PASS: Use SELECT * or explicitly include new columns const { data } = await supabase . from ( "users" ) . select ( "*" ) . single (); Pattern 3: Error State Leakage Frequency : Moderate — when adding error handling to existing components // FAIL: Error state set but old data not cleared catch (err) { setError ( "Failed to load" ); // reservations still shows data from previous tab! } // PASS: Clear related state on error catch (err) { setReservations ([]); // Clear stale data setError ( "Failed to load" ); } Pattern 4: Optimistic Update Without Proper Rollback // FAIL: No rollback on failure const handleRemove = async ( id : string ) => { setItems ( prev => prev. filter ( i => i. id !== id)); await fetch ( `/api/items/ ${id} ` , { method : "DELETE" }); // If API fails, item is gone from UI but still in DB }; // PASS: Capture previous state and rollback on failure const handleRemove = async ( id : string ) => { const prevItems = [...items]; setItems ( prev => prev. filter ( i => i. id !== id)); try { const res = await fetch ( `/api/items/ ${id} ` , { method : "DELETE" }); if (!res. ok ) throw new Error ( "API error" ); } catch { setItems (prevItems); // Rollback alert ( "削除に失敗しました" ); } }; Strategy: Test Where Bugs Were Found Don't aim for 100% coverage. Instead: Bug found in /api/user/profile → Write test for profile API Bug found in /api/user/messages → Write test for messages API Bug found in /api/user/favorites → Write test for favorites API No bug in /api/user/notifications → Don't write test (yet) Why this works with AI development: AI tends to make the same category of mistake repeatedly Bugs cluster in complex areas (auth, multi-path logic, state management) Once tested, that exact regression cannot happen again Test count grows organically with bug fixes — no wasted effort Quick Reference AI Regression Pattern Test Strategy Priority Sandbox/production mismatch Assert same response shape in sandbox mode High SELECT clause omission Assert all required fields in response High Error state leakage Assert state cleanup on error Medium Missing rollback Assert state restored on API failure Medium Type cast masking null Assert field is not undefined Medium DO / DON'T DO: Write tests immediately after finding a bug (before fixing it if possible) Test the API response shape, not the implementation Run tests as the first step of every bug-check Keep tests fast (< 1 second total with sandbox mode) Name tests after the bug they prevent (e.g., "BUG-R1 regression") DON'T: Write tests for code that has never had a bug Trust AI self-review as a substitute for automated tests Skip sandbox path testing because "it's just mock data" Write integration tests when unit tests suffice Aim for coverage percentage — aim for regression prevention
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