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@hoshinotsuyoshi hoshinotsuyoshi commented Sep 26, 2025

Summary

  • Added explicit Sentry error reporting for SQL syntax errors in the saveTestcase tool
  • SQL errors are now properly tracked in Sentry while maintaining LangGraph's retry mechanism

Issue

  • resolves: route06/liam-internal#5724

Why is this change needed?

Previously, SQL syntax errors in the validateSqlSyntax function were not being sent to Sentry, even though the tool was wrapped with withSentryCaptureException. This was because these errors are intentionally thrown to trigger LangGraph's retry mechanism, and the wrapper would capture and re-throw them without special handling for monitoring purposes.

Changes

  • Import @sentry/node in saveTestcaseTool.ts
  • Add explicit Sentry.captureException() call when SQL syntax validation fails
  • Include appropriate tags (errorType: 'sql_syntax_error', toolName: 'saveTestcase')
  • Pass additional context including the actual SQL query and parse error message

Test plan

  • All existing tests pass
  • Linting and formatting pass
  • Manual testing: Verify that SQL syntax errors are now reported to Sentry

🤖 Generated with Claude Code

Summary by CodeRabbit

  • Chores
    • Implemented enhanced error monitoring for SQL parsing failures in the QA test case saving tool, capturing exceptions with structured context and tags.
    • Records errors before triggering existing retry logic, improving observability and triage without altering user flows.
    • Facilitates faster diagnosis of malformed queries encountered during automated processing.
    • No user-facing behavior changes; background telemetry only.

…eTestcase tool

Previously, SQL syntax errors were not being sent to Sentry even though they were
wrapped with withSentryCaptureException. This was because these errors are
intentionally thrown to trigger LangGraph's retry mechanism.

Now explicitly capturing SQL syntax errors in Sentry before re-throwing them,
allowing us to monitor these errors while maintaining the retry behavior.

- Added Sentry.captureException() call with appropriate tags and context
- Tags include errorType: 'sql_syntax_error' and toolName: 'saveTestcase'
- Extra context includes the actual SQL query and parse error message

Fixes #5724

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
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coderabbitai bot commented Sep 26, 2025

Walkthrough

Adds Sentry error monitoring to saveTestcaseTool: when pgParse reports a SQL syntax error, the code captures the exception with tags and extras via @sentry/node, then rethrows to preserve the existing retry flow.

Changes

Cohort / File(s) Summary
Error monitoring integration
frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts
Import @sentry/node; on pgParse error, create Error, add tags/extras (errorType: sql_syntax_error, toolName: saveTestcase, sql, parseError), call Sentry.captureException, then throw the error to trigger existing retries.

Sequence Diagram(s)

sequenceDiagram
  autonumber
  participant Tool as saveTestcaseTool
  participant Parser as pgParse
  participant Sentry as Sentry SDK
  participant Retry as Retry Mechanism

  Tool->>Parser: parse(sql)
  alt parse error
    Parser-->>Tool: { error }
    Tool->>Sentry: captureException(err, tags/extras)
    Tool-->>Retry: throw err
    Retry->>Tool: retry according to existing policy
  else parse ok
    Parser-->>Tool: { ast }
    Tool-->>Tool: continue normal flow
  end
Loading

Estimated code review effort

🎯 2 (Simple) | ⏱️ ~10 minutes

Possibly related PRs

Suggested reviewers

  • FunamaYukina
  • junkisai
  • NoritakaIkeda

Poem

A rabbit taps the keys with care,
When SQL stumbles, we’re aware.
Sentry hears the syntax sneeze,
Tags and extras, logged with ease.
Retry hops in, swift and spry—
Tests saved safe, and errors fly. 🐇✨

Pre-merge checks and finishing touches

✅ Passed checks (3 passed)
Check name Status Explanation
Title Check ✅ Passed The title succinctly describes the primary change by indicating that explicit Sentry error reporting is being added for SQL syntax errors in the saveTestcase tool, directly reflecting the main updates in the pull request. It clearly identifies both the mechanism (Sentry error reporting) and the context (SQL syntax errors in saveTestcase), making it easily understandable at a glance. The phrasing is concise and free of extraneous terms, so reviewers can quickly grasp the scope of the change.
Description Check ✅ Passed The description correctly includes the "## Issue" section with the issue reference and a "## Why is this change needed?" section providing the rationale as required by the template. It also enhances clarity with a summary, detailed changes, and a test plan, which align well with common repository practices. Overall, the PR description satisfies the template requirements and clearly communicates the intent and scope of the changes.
Docstring Coverage ✅ Passed No functions found in the changes. Docstring coverage check skipped.
✨ Finishing touches
  • 📝 Generate Docstrings
🧪 Generate unit tests
  • Create PR with unit tests
  • Post copyable unit tests in a comment
  • Commit unit tests in branch sentry-validate-sql

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Actionable comments posted: 0

🧹 Nitpick comments (1)
frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts (1)

55-64: Standardize Sentry tagging conventions

  • Centralize tag setup in a shared helper using Sentry.withScope and scope.setTag for low-cardinality metadata.
  • Move high-cardinality or sensitive data (e.g. full SQL, parse errors) into extra or contexts.
  • Adopt consistent kebab-case tag keys (e.g. error-type, tool-name) and document all canonical tags in a repo guideline.
📜 Review details

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📒 Files selected for processing (1)
  • frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts (2 hunks)
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**/*.ts

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Name utility files in camelCase (e.g., mergeSchema.ts)

Files:

  • frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts
**/*.{ts,tsx}

📄 CodeRabbit inference engine (AGENTS.md)

Use TypeScript/TSX across the codebase

**/*.{ts,tsx}: Prefer early returns for readability
Use named exports only (no default exports)
Prefer const arrow functions over function declarations for simple utilities (e.g., const toggle = () => {})

Files:

  • frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts
frontend/internal-packages/**

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Infra and tooling (e2e, configs, storybook, agent) live under frontend/internal-packages

Files:

  • frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts
frontend/**/*.{ts,tsx}

📄 CodeRabbit inference engine (CLAUDE.md)

Follow existing import patterns and tsconfig path aliases

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🔇 Additional comments (2)
frontend/internal-packages/agent/src/qa-agent/tools/saveTestcaseTool.ts (2)

8-8: LGTM! Import follows naming conventions.

The Sentry import follows the established pattern in the codebase and is correctly scoped to the specific functionality being added.


48-68: Approve SQL syntax error capture in Sentry
Sentry is initialized across the project and the explicit captureException call with custom tags here aligns with existing patterns while preserving the retry flow.

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github-actions bot commented Sep 26, 2025

🤖 Agent Deep Modeling Execution

Processing time: 6m 6s
Started at: 2025-09-26 12:28:26 UTC

Command Output

@liam-hq/agent@0.1.0 execute-deep-modeling /home/runner/work/liam/liam/frontend/internal-packages/agent
pnpm test:integration src/createGraph.integration.test.ts

@liam-hq/agent@0.1.0 test:integration /home/runner/work/liam/liam/frontend/internal-packages/agent
vitest --watch=false --passWithNoTests --config vitest.config.integration.ts src/createGraph.integration.test.ts

RUN v3.2.4 /home/runner/work/liam/liam/frontend/internal-packages/agent

(node:7630) ExperimentalWarning: WASI is an experimental feature and might change at any time
(Use node --trace-warnings ... to show where the warning was created)

✅ [INFO] 2025-09-26T12:28:29.502Z
LangSmith Trace URL: https://smith.langchain.com/o/eed4d2d8-0bd8-4ca4-a452-4da88ef63fd6/projects/p/99d63e81-58f9-475a-8985-409b591e26b0?searchModel=%7B%22filter%22%3A%22and(eq(is_root%2C%20true)%2C%20and(eq(metadata_key%2C%20%5C%22thread_id%5C%22)%2C%20eq(metadata_value%2C%20%5C%221e9919ee-52c7-4a72-a336-5fb62a155577%5C%22)))%22%7D

⏺ (pm):

Planned action: Analyze the request and create a production-ready BRD with assumptions and structured functional requirements; then save the summarized business requirement and categorized functional requirements to the artifact tool.

🔧 saveRequirementsToArtifactTool(businessRequirement: "Deliver a simple,...", functionalRequirements: {12 keys}) ⎿ unknown: Requirements saved successfully to artifact

🔧 schemaDesignTool(operations: [8 items])

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

⏺ (qa):

{
"testcaseWithDml": {
"requirementType": "functional",
"requirementCategory": "Administration",
"requirement": "The system must allow admins to unlock locked accounts and view lock reasons.",
"title": "Admins can unlock locked accounts and view lock reasons via audit trail",
"description": "This test covers: (1) creating a locked user with a future lock window, (2) recording the lock reason in audit_events, (3) performing an admin-like unlock (status -> active, locked_until -> NULL), (4) recording the unlock audit event, and (5) validating final unlocked state and accessibility of the lock reason via audit trail.",
"dmlOperation": {
"operation_type": "INSERT",
"sql": "\n-- Step 1: Create a locked user and capture its id/email via a RETURNING in a CTE\nWITH locked_user AS (\n INSERT INTO users (\n id,\n email,\n phone,\n status,\n username,\n last_name,\n created_at,\n deleted_at,\n first_name,\n updated_at,\n locked_until,\n last_login_at,\n password_hash,\n email_verified,\n deletion_expires_at,\n failed_login_attempts,\n last_password_change_at\n ) VALUES (\n gen_random_uuid(),\n CONCAT('locked_user_', gen_random_uuid(), '@example.com'),\n NULL,\n 'locked'::user_status,\n NULL,\n 'Locke',\n now(),\n NULL,\n 'Locked',\n now(),\n now() + INTERVAL '12 hours',\n NULL,\n NULL,\n TRUE,\n NULL,\n 5,\n NULL\n )\n RETURNING id, email\n)\n-- Step 2: Log the lock reason in audit_events referencing the newly created user\nINSERT INTO audit_events (\n id,\n actor_id,\n metadata,\n event_type,\n ip_address,\n actor_email,\n occurred_at,\n target_user_id,\n target_user_email\n)\nSELECT\n gen_random_uuid(),\n NULL,\n '{"reason": "Too many failed login attempts"}'::jsonb,\n 'user.locked',\n NULL,\n NULL,\n now(),\n locked_user.id,\n locked_user.email\nFROM locked_user;\n\n-- Step 3: Unlock the user as an admin action (admin-like UPDATE)\nWITH unlocked AS (\n UPDATE users\n SET status = 'active'::user_status,\n locked_until = NULL,\n updated_at = now()\n WHERE email LIKE 'locked_user_%@example.com'\n RETURNING id, email\n)\n-- Step 4: Log the unlock action in audit_events\nINSERT INTO audit_events (\n id,\n actor_id,\n metadata,\n event_type,\n ip_address,\n actor_email,\n occurred_at,\n target_user_id,\n target_user_email\n)\nSELECT\n gen_random_uuid(),\n NULL,\n '{"action": "admin_unlock"}'::jsonb,\n 'user.unlocked',\n NULL,\n NULL,\n now(),\n unlocked.id,\n unlocked.email\nFROM unlocked;\n\n-- Step 5: Optional final check to validate final unlocked state\nSELECT id, email, status, locked_until FROM users WHERE email LIKE 'locked_user_%@example.com';\n",
"description": "Set up a locked user, log the lock reason, perform an admin-like unlock, log the unlock, and verify final state."
}
}
}

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys})

⏺ (qa):

{
"testcaseWithDml": {
"requirementType": "functional",
"requirementCategory": "Data Model Requirements",
"requirement": "The system must prevent orphaned references when users or roles are deleted (e.g., cascading or constraints as appropriate).",
"title": "Test: Prevent orphaned references on user and role deletions via cascade or constraints",
"description": "This test validates that deleting user accounts and role entries does not leave orphan references across related tables (user_roles, tokens, sessions, audit_events). It exercises both sides of the deletion path: removing a user should cascade or set NULL on dependent rows, and removing a role should similarly affect dependent user_roles. The test uses gen_random_uuid() to generate all UUIDs and runs within a transaction, rolling back at the end to avoid persisting test data.",
"dmlOperation": {
"operation_type": "INSERT",
"sql": "BEGIN;\n\nDO $$\nDECLARE\n u_id UUID := gen_random_uuid();\n r_id UUID := gen_random_uuid();\n ur_id UUID;\n t_id UUID;\n s_id UUID;\n a_id UUID;\n orphan_ur INT;\n orphan_t INT;\n orphan_s INT;\n orphan_a_actor INT;\n orphan_a_target INT;\n orphan_ur_role INT;\nBEGIN\n -- Insert a test user\n INSERT INTO users (id, email, status, last_name, created_at, updated_at, first_name, email_verified, failed_login_attempts)\n VALUES (u_id, 'orphan_test_user@example.com', 'active'::user_status, 'Test', now(), now(), 'Orphan', true, 0);\n\n -- Insert a test role\n INSERT INTO roles (id, name, created_at, updated_at, system_role)\n VALUES (r_id, 'OrphanTestRole', now(), now(), true);\n\n -- Link user to role\n ur_id := gen_random_uuid();\n INSERT INTO user_roles (id, user_id, role_id, assigned_at)\n VALUES (ur_id, u_id, r_id, now());\n\n -- Create a token for the user\n t_id := gen_random_uuid();\n INSERT INTO tokens (id, type, user_id, created_at, expires_at, token_hash, consumed_at)\n VALUES (t_id, 'email_verification'::token_type, u_id, now(), now() + interval '1 day', 'hash_placeholder', NULL);\n\n -- Create a session for the user\n s_id := gen_random_uuid();\n INSERT INTO sessions (id, revoked, user_id, created_at, expires_at, session_token, last_activity_at)\n VALUES (s_id, false, u_id, now(), now() + interval '2 hours', 'sess_placeholder', now());\n\n -- Create an audit event referencing the user\n a_id := gen_random_uuid();\n INSERT INTO audit_events (id, actor_id, metadata, event_type, ip_address, actor_email, occurred_at, target_user_id, target_user_email)\n VALUES (a_id, u_id, '{}'::jsonb, 'user.created', '127.0.0.1', 'orphan_test_user@example.com', now(), u_id, 'orphan_test_user@example.com');\n\n -- Delete the user\n DELETE FROM users WHERE id = u_id;\n\n -- Check for orphaned references\n SELECT COUNT() INTO orphan_ur FROM user_roles WHERE user_id = u_id;\n SELECT COUNT() INTO orphan_t FROM tokens WHERE user_id = u_id;\n SELECT COUNT() INTO orphan_s FROM sessions WHERE user_id = u_id;\n SELECT COUNT() INTO orphan_a_actor FROM audit_events WHERE actor_id = u_id;\n SELECT COUNT() INTO orphan_a_target FROM audit_events WHERE target_user_id = u_id;\n\n RAISE NOTICE 'Orphans after user delete: user_roles=%, tokens=%, sessions=%, audit_actor=%, audit_target=%', orphan_ur, orphan_t, orphan_s, orphan_a_actor, orphan_a_target;\n\n -- Delete the role\n DELETE FROM roles WHERE id = r_id;\n\n -- Check for orphaned user_roles referencing the deleted role\n SELECT COUNT() INTO orphan_ur_role FROM user_roles WHERE role_id = r_id;\n RAISE NOTICE 'Orphans after role delete: user_roles_for_role=%', orphan_ur_role;\n\nEND;\n$$ LANGUAGE plpgsql;\n\nROLLBACK;\n",
"description": "This DO-based script creates a test user and a test role, links them, and creates dependent records (tokens, sessions, audit events). It then deletes the user and checks for any orphaned references in child tables. It also deletes the role and checks orphaned references for user_roles referencing that role. The entire script runs inside a transaction that is rolled back to avoid persisting test data."
}
}
}

🔧 saveTestcase(testcaseWithDml: {6 keys})

🔧 saveTestcase(testcaseWithDml: {6 keys}) ⎿ unknown: 36/48 test cases passed, 12 failed

Test Case: Users can view and update their own profile fields while protecting system-managed fields

1. Error: insert or update on table "user_roles" violates foreign key constraint "fk_user_roles_user"

-- Assign the test role to Alice
INSERT INTO user_roles (id, role_id, user_id, assigned_at, assigned_by)
SELECT gen_random_uuid(), (SELECT id FROM roles WHERE name = 'TestUserRole'), (SELECT id FROM test_user_ids WHERE name = 'alice'), now(), NULL

Test Case: Functional test: Email-and-password login readiness for Admin and EndUser with role assignments and negative locked user

1. Error: relation "end_user" does not exist

-- Test Case: 5c6bf480-6fa2-4da3-916a-a8e7de98ba2a
-- Functional test: Email-and-password login readiness for Admin and EndUser with role assignments and negative locked user
-- Initial data setup for authenticating admin and end-user via email/password; includes role assignments and a locked-user negative case to validate access restrictions.
WITH admin_role AS (
  INSERT INTO roles (id, name, created_at, updated_at, system_role, description)
  VALUES (gen_random_uuid(), 'Admin', now(), now(), true, 'System admin role with full permissions')
  RETURNING id
),
enduser_role AS (
  INSERT INTO roles (id, name, created_at, updated_at, system_role, description)
  VALUES (gen_random_uuid(), 'User', now(), now(), false, 'Regular user role')
  RETURNING id
),
admin_user AS (
  INSERT INTO users (id, email, status, last_name, first_name, created_at, updated_at, email_verified, failed_login_attempts, password_hash)
  VALUES (gen_random_uuid(), 'admin@example.com', 'active', 'Admin', 'Alice', now(), now(), true, 0, 'pbkdf2$admin')
  RETURNING id
),
eend_user AS (
  INSERT INTO users (id, email, status, last_name, first_name, created_at, updated_at, email_verified, failed_login_attempts, password_hash)
  VALUES (gen_random_uuid(), 'user@example.com', 'active', 'User', 'Bob', now(), now(), true, 0, 'pbkdf2$user')
  RETURNING id
)
INSERT INTO user_roles (id, role_id, user_id, assigned_at, assigned_by)
SELECT gen_random_uuid(), admin_role.id, admin_user.id, now(), NULL
FROM admin_role, admin_user
UNION ALL
SELECT gen_random_uuid(), enduser_role.id, end_user.id, now(), NULL
FROM enduser_role, end_user

Test Case: Password policy enforcement with set/reset confirmation (positive, edge, and negative scenarios)

1. Error: column "metadata" of relation "tokens" does not exist

-- Password reset tokens. New_passwords are provided in metadata for policy checks by the test DO block.
INSERT INTO tokens (
  id, type, user_id, created_at, expires_at, token_hash, metadata, consumed_at
) VALUES
  (gen_random_uuid(), 'password_reset', (SELECT id FROM users WHERE email = 'alice@example.com'), NOW() - INTERVAL '2 hours', NOW() + INTERVAL '1 day', 'tok1', '{"confirmed": true, "new_password": "NewPassw0rd"}', NULL),
  (gen_random_uuid(), 'password_reset', (SELECT id FROM users WHERE email = 'bob@example.com'), NOW() - INTERVAL '3 hours', NOW() + INTERVAL '1 day', 'tok2', '{"confirmed": false, "new_password": "Passw0rd8"}', NULL),
  (gen_random_uuid(), 'password_reset', (SELECT id FROM users WHERE email = 'alice@example.com'), NOW() - INTERVAL '1 hour', NOW() + INTERVAL '1 day', 'tok3', '{"confirmed": true, "new_password": "badpw"}', NULL)

Test Case: Test: Session sign-out and inactivity timeout (30-minute rule) for authentication

1. Error: relation "u" does not exist

-- Validation: Query all sessions for the test user to verify revoke state and activity timestamps
SELECT id, revoked, last_activity_at
FROM sessions
WHERE user_id = (SELECT id FROM u)
ORDER BY last_activity_at DESC

Test Case: Admin dashboard: list users with pagination, sortable columns, and quick actions

1. Error: column "status" is of type user_status but expression is of type text

-- Test Case: 19178971-b3e4-4868-8dea-ab738ea9e298
-- Admin dashboard: list users with pagination, sortable columns, and quick actions
-- Seed 15 users to exercise pagination (assuming a page size of 10). Create an admin test user and perform quick actions (edit, deactivate, reactivate, reset password, and resend verification) in a single PL/pgSQL block. Finally, run pagination queries to validate ordering and page boundaries.
-- 1) Insert 15 test users with deterministic timestamps for pagination tests
INSERT INTO users (id, email, status, last_name, created_at, updated_at, first_name, email_verified, failed_login_attempts, username)
SELECT gen_random_uuid(),
       'test-user-' || s.i || '-' || replace(gen_random_uuid()::text, '-', '') || '@example.com',
       CASE WHEN s.i % 3 = 0 THEN 'inactive' WHEN s.i % 3 = 1 THEN 'active' ELSE 'pending' END,
       'Last' || s.i,
       now() - ((15 - s.i) * interval '1 minute'),
       now() - ((15 - s.i) * interval '1 minute'),
       'First' || s.i,
       CASE WHEN s.i <= 5 THEN false ELSE true END,
       0,
       CASE WHEN s.i % 2 = 0 THEN 'user' || s.i ELSE NULL END
FROM generate_series(1, 15) AS s(i)

Test Case: Admin-created user: direct creation bypassing self-registration with optional temporary password

1. Error: INSERT has more expressions than target columns

-- Admin creates a second user directly, with no temporary password
INSERT INTO users (
  id,
  email,
  phone,
  status,
  username,
  last_name,
  first_name,
  created_at,
  updated_at,
  deleted_at,
  locked_until,
  last_login_at,
  password_hash,
  email_verified,
  deletion_expires_at,
  failed_login_attempts,
  last_password_change_at
) VALUES (
  gen_random_uuid(),
  'admin_created_user2@example.com',
  NULL,
  'pending'::user_status,
  'admin_created_user2',
  'Smith',
  'Alice',
  now(),
  now(),
  NULL,
  NULL,
  NULL,
  NULL,
  NULL,
  TRUE,
  NULL,
  0,
  NULL
)

Test Case: Sort verification across name, email, created_at, last_login_at, and status with comprehensive positive and negative coverage

1. Error: VALUES lists must all be the same length

-- 1) Insert test users
INSERT INTO users (id, email, phone, status, username, last_name, created_at, deleted_at, first_name, updated_at, locked_until, last_login_at, password_hash, email_verified, deletion_expires_at, failed_login_attempts, last_password_change_at)
VALUES
  (gen_random_uuid(), 'john.doe@example.com', '555-0100', 'active'::user_status, 'jdoe', 'Doe', now() - interval '5 days', NULL, 'John', now() - interval '5 days', NULL, now() - interval '1 day', NULL, true, NULL, 0, NULL),
  (gen_random_uuid(), 'alice.smith@example.com', NULL, 'pending'::user_status, NULL, 'Smith', now() - interval '3 days', NULL, 'Alice', now() - interval '3 days', NULL, NULL, NULL, true, NULL, 0, NULL),
  (gen_random_uuid(), 'bob.adams@example.com', NULL, 'inactive'::user_status, 'bobA', 'Adams', now() - interval '2 days', NULL, 'Bob', now() - interval '2 days', NULL, now() - interval '2 hours', NULL, NULL, true, NULL, 0, NULL),
  (gen_random_uuid(), 'charlie.brown@example.com', NULL, 'active'::user_status, 'cbrown', 'Brown', now() - interval '1 day', NULL, 'Charlie', now() - interval '1 day', NULL, now() - interval '12 hours', NULL, NULL, true, NULL, 0, NULL),
  (gen_random_uuid(), 'ada.lee@example.com', NULL, 'locked'::user_status, 'adaL', 'Lee', now() - interval '4 days', NULL, 'Ada', now() - interval '4 days', NULL, NULL, NULL, true, NULL, 0, NULL)

Test Case: Admin-resend flows for verification and password reset emails

1. Error: invalid input value for enum token_type: "EMAIL_VERIFICATION"

-- Email verification token for unverified user
INSERT INTO tokens (
  id, type, user_id, created_at, expires_at, token_hash, consumed_at
) VALUES (
  gen_random_uuid(),
  'EMAIL_VERIFICATION'::token_type,
  (SELECT id FROM users WHERE email='unverified_user@example.com'),
  now(),
  now() + interval '24 hours',
  'hash_' || replace(gen_random_uuid()::text, '-', ''),
  NULL
)

Test Case: Audit log tamper protection: restrict DML on audit_events to admin only

1. Error: Missing role: audit_admin

-- Test Case: 72a1f125-bd1d-4b88-95c9-8a5e2c1468d5
-- Audit log tamper protection: restrict DML on audit_events to admin only
-- Tests that non-admin users cannot insert, update, or delete rows in audit_events, while admins can. It uses a temp table to share the created log id across role switches. Gen UUIDs are created with gen_random_uuid() and timestamps with now().
-- Ensure required extension for UUID generation


-- Precondition: require certain roles exist in the environment
DO $$
BEGIN
  IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname = 'audit_admin') THEN
    RAISE EXCEPTION 'Missing role: audit_admin';
  END IF;
  IF NOT EXISTS (SELECT 1 FROM pg_roles WHERE rolname = 'audit_user') THEN
    RAISE EXCEPTION 'Missing role: audit_user';
  END IF;
END$$

Test Case: Verify salted, one-way password hashing using crypt() with pgcrypto and salt

1. Error: function gen_salt(unknown) does not exist

-- Test Case: 403fa532-f11f-48ea-b6ff-ae2461534b5b
-- Verify salted, one-way password hashing using crypt() with pgcrypto and salt
-- Inserts and updates to validate that password_hash is a salted hash produced by crypt(), and that verification using crypt() succeeds. Includes edge-case and soft-invite cases, plus a controlled duplicate email check via a DO block that handles exceptions gracefully.


-- 1) Insert a user with a securely hashed password (salted)
INSERT INTO users (id, email, status, first_name, last_name, created_at, updated_at, email_verified, failed_login_attempts, password_hash, last_password_change_at)
VALUES (
  gen_random_uuid(),
  'alice_security_hash@example.com',
  'active'::user_status,
  'Alice',
  'Anderson',
  now(),
  now(),
  TRUE,
  0,
  crypt('Secur3P@ss', gen_salt('bf')),
  now()
)

Test Case: Test rate-limiting for authentication and password reset endpoints

1. Error: column "actor_id" is of type uuid but expression is of type text

-- Test Case: ee5180f3-eb15-40f5-aa6a-51c74df34b4b
-- Test rate-limiting for authentication and password reset endpoints
-- Seed a test user and perform 5 consecutive failed authentication events to trigger rate-limiting behavior, updating failed_login_attempts and setting locked_until. Then generate 5 password_reset tokens for the user within the rate-limiting window to model password reset request throttling. The block uses gen_random_uuid() for all UUID fields and ties audit_events and tokens to the same new_user via RETURNING id. This test provides a reproducible state to validate that rate-limiting logic would block further sensitive requests within the window and that counters and timestamps reflect throttling semantics.
WITH new_user AS (
  INSERT INTO users (
    id, email, phone, status, username, last_name, created_at, deleted_at, first_name, updated_at, locked_until, last_login_at, password_hash, email_verified, deletion_expires_at, failed_login_attempts, last_password_change_at
  )
  VALUES (
    gen_random_uuid(),
    'rate-limit-user@example.com',
    NULL,
    'active',
    NULL,
    'Limiter',
    NOW(),
    NULL,
    'RateLimiter',
    NOW(),
    NULL,
    NULL,
    NULL,
    TRUE,
    NULL,
    0,
    NULL
  )
  RETURNING id, email
),
failed_events AS (
  INSERT INTO audit_events (id, actor_id, metadata, event_type, ip_address, actor_email, occurred_at, target_user_id, target_user_email)
  SELECT gen_random_uuid(), NULL, NULL, 'auth.login_failed', NULL, NULL, NOW() - interval '9 minutes', (SELECT id FROM new_user), (SELECT email FROM new_user)
  UNION ALL
  SELECT gen_random_uuid(), NULL, NULL, 'auth.login_failed', NULL, NULL, NOW() - interval '7 minutes', (SELECT id FROM new_user), (SELECT email FROM new_user)
  UNION ALL
  SELECT gen_random_uuid(), NULL, NULL, 'auth.login_failed', NULL, NULL, NOW() - interval '6 minutes', (SELECT id FROM new_user), (SELECT email FROM new_user)
  UNION ALL
  SELECT gen_random_uuid(), NULL, NULL, 'auth.login_failed', NULL, NULL, NOW() - interval '5 minutes', (SELECT id FROM new_user), (SELECT email FROM new_user)
  UNION ALL
  SELECT gen_random_uuid(), NULL, NULL, 'auth.login_failed', NULL, NULL, NOW() - interval '4 minutes', (SELECT id FROM new_user), (SELECT email FROM new_user)
),
update_user AS (
  UPDATE users SET failed_login_attempts = 5, locked_until = NOW() + interval '15 minutes', updated_at = NOW()
  WHERE id = (SELECT id FROM new_user)
),
tokens AS (
  INSERT INTO tokens (id, type, user_id, created_at, expires_at, token_hash, consumed_at)
  SELECT gen_random_uuid(), 'password_reset', (SELECT id FROM new_user), NOW() - interval '50 minutes', NOW() - interval '50 minutes' + interval '1 hour', md5(gen_random_uuid()::text), NULL
  UNION ALL
  SELECT gen_random_uuid(), 'password_reset', (SELECT id FROM new_user), NOW() - interval '40 minutes', NOW() - interval '40 minutes' + interval '1 hour', md5(gen_random_uuid()::text), NULL
  UNION ALL
  SELECT gen_random_uuid(), 'password_reset', (SELECT id FROM new_user), NOW() - interval '30 minutes', NOW() - interval '30 minutes' + interval '1 hour', md5(gen_random_uuid()::text), NULL
  UNION ALL
  SELECT gen_random_uuid(), 'password_reset', (SELECT id FROM new_user), NOW() - interval '20 minutes', NOW() - interval '20 minutes' + interval '1 hour', md5(gen_random_uuid()::text), NULL
  UNION ALL
  SELECT gen_random_uuid(), 'password_reset', (SELECT id FROM new_user), NOW() - interval '10 minutes', NOW() - interval '10 minutes' + interval '1 hour', md5(gen_random_uuid()::text), NULL
)
SELECT 1

Test Case: Admin vs Non-Admin visibility: deleted and inactive users hidden for non-admins

1. Error: invalid input syntax for type boolean: ""

CREATE POLICY app_visibility ON users FOR SELECT USING (
  (current_setting('app.role','') = 'admin') OR (status = 'active')
)

⏺ (lead):

Here is a concise recap of what was accomplished in this database design session.

  • Main requirements analyzed

    • Build a simple, secure user management system with:
      • User registration, profile management, and lifecycle (activate, deactivate, pending, locked, deleted with soft-delete window)
      • Authentication (email/password with verification, password policy, login throttling, session handling)
      • Authorization via role-based access control (RBAC) with Admin and User roles, multiple roles per user
      • Admin capabilities (user management, role assignment, audit visibility, bulk actions)
      • Auditing and reporting (audit logs, export, metrics, dashboards)
      • Data retention/privacy (soft-delete window, restore, hard delete, data anonymization)
      • Notifications (verification, welcome, password reset; admin alerts)
      • Search, filter, export (CSV exports with applied filters)
      • Security/compliance basics (password hashing, TLS emphasis, RBAC checks, rate limiting)
    • Data model constraints (uniqueness on email, unique username when present, non-null essential fields)
  • Key database design decisions

    • Enumerations to enforce lifecycle states and token purposes:
      • user_status: pending, active, inactive, locked, deleted
      • token_type: email_verification, password_reset
    • Core entities and relationships:
      • Users table with profile and system-managed fields (created_at, updated_at, last_login_at, last_password_change_at, etc.)
      • Roles table for RBAC
      • UserRoles join table to support many-to-many user-role assignments
      • Tokens table for single-use tokens (email_verification, password_reset) with TTLs and consumed flag
      • Sessions table for persistent user sessions (hashed tokens, timeout, revoke)
      • AuditEvents table to log security/administrative actions
    • Lifecycle and security features:
      • Soft-delete support via deleted_at and deletion_expires_at
      • Passwords stored as one-way hashes with salt
      • Rate limiting hooks via failed_login_attempts and locked_until
    • Data integrity and performance:
      • Foreign keys with cascading deletes where appropriate
      • Unique indexes on email and username (when provided)
      • Various indexes to support common queries (by email, username, status, created_at, last_login_at, role associations, audit movement)
    • Data retention and privacy:
      • Mechanisms for restore within retention window, and hard delete after expiry
      • Auditability preserved for compliance
  • Schemas, tables, or data structures created or modified

    • Enums added:
      • user_status (pending, active, inactive, locked, deleted)
      • token_type (email_verification, password_reset)
    • Tables created:
      • users with comprehensive profile and lifecycle fields
      • roles (RBAC catalog)
      • user_roles (join table for many-to-many User ↔ Role)
      • tokens (password_reset and email_verification tokens)
      • sessions (persistent user sessions)
      • audit_events (append-only style for security/admin events)
    • Additional design elements:
      • Indexes on users (email, username, status, created_at, last_login_at)
      • Indexes on roles, user_roles, audit_events, tokens, sessions
      • Foreign key constraints linking users, roles, tokens, sessions, and audit events
    • Notable column choices:
      • Timestamps with time zone
      • UUIDs generated via gen_random_uuid()
      • Password_hash stored securely; password change tracking
      • Metadata fields (JSONB) in audit_events and tokens for extensibility
  • Important outcomes or results

    • Schema updated and versioned; DDL validation completed (all statements executed)
    • A comprehensive set of functional test cases and DML scripts were created to validate:
      • User lifecycle (create, view, update, deactivate, soft-delete, restore)
      • Unique constraints (email, username)
      • Profile updates with system-managed fields protected
      • Email verification and password reset flows
      • RBAC integrity (Admin/User roles, multiple roles, self-privilege elevation prevention, admin actions)
      • Admin actions (bulk operations, admin-created users, role assignments/revocations)
      • Audit logging coverage and querying with filters
      • Security controls (throttling, login failures, forced logout, token handling, password hashing)
      • Data retention flows (soft-delete, restore, hard delete, anonymization)
      • Admin-only exports with audit trails
      • Verification of data visibility (admin vs non-admin views)
    • Test run status
      • A large suite of test cases were created and saved; a run reported 36/48 tests passed, with several failures due to relational constraints, enum handling, and some test syntax mismatches. These issues indicate next steps to align test scaffolding with the final schema (e.g., correct FK targets, enum casting, and role setup).
    • Overall achievement
      • A robust, extensible user management schema aligned with the analyzed requirements, including RBAC, auditing, token-based flows, and lifecycle controls, along with a broad suite of tests and examples to validate behavior and compliance.

If you’d like, I can:

  • Summarize specific schemas or show a compact ER diagram outline
  • Produce a migration plan or a checklist to fix the failing test cases
  • Extract a minimal, ready-to-run DDL snippet for a baseline deployment
  • Create a quick-reference mapping of enums, tables, and key columns for quick onboarding·

Test Files 1 passed (1)
Tests 1 passed (1)
Start at 12:28:27
Duration 364.28s (transform 468ms, setup 0ms, collect 1.46s, tests 362.53s, environment 0ms, prepare 83ms)

Status: Completed successfully

Finished at: 2025-09-26 12:34:32 UTC

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