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Automated testing

オープン
#206 コメント 0 件 リアクション 0 件 担当者 0 名 GitHub で見る

まだ誰も着手していません。

評価

難易度
5/5
見積もり時間
1週間以上
初心者へのやさしさ
25/100
issue の種類
機能追加
明瞭さ
説明が足りない
活発さ
停滞
技術スタック
cypress, github-actions, javascript, postgresql, supabase

調査の方向性

まず docs/PRDs/206-automated-testing.md を読み、リポジトリに既存のテストおよび GitHub Actions の設定を確認します。issue では候補ツールとして Jest、Supertest、Cypress が挙げられています。完了条件は、決定論的な unit、integration、E2E テストスイートが CI に統合され、80% を超えるカバレッジを達成し、リグレッションとセキュリティのカバレッジを含み、テストドキュメントが整備されていることです。

索引モデルが issue の本文から書いたものです。

説明

cicd hacktoberfest

📋 Product Requirements Document

PRD: Automated testing

Issue: #206
Milestone: Phase 9: Deployment & Operations
Labels: cicd, hacktoberfest


PRD: Automated Testing for MeshHook

Overview

The MeshHook project, a webhook-first, deterministic, Postgres-native workflow engine, requires a robust automated testing framework to ensure high-quality and reliable software delivery. The implementation of an automated testing suite is imperative to detect bugs early, streamline the development process, and maintain the integrity of key features such as webhook triggers, visual DAG builders, durable runs, live logs, and multi-tenant RLS security.

Purpose

This PRD outlines the development and integration of a comprehensive automated testing suite aimed at unit, integration, and end-to-end (E2E) tests. This suite will support continuous integration and delivery (CI/CD) processes, enhance deployment reliability, and safeguard against regressions.

Alignment with Project Goals

Automated testing is pivotal for:

  • Ensuring the security and reliability of the webhook triggers alongside their signature verification process.
  • Validating the functionality and user experience of the visual DAG builder.
  • Preserving the integrity and accuracy of durable, replayable runs.
  • Confirming the real-time capabilities of live logs through Supabase Realtime.
  • Maintaining the robustness of the multi-tenant RLS security model.

Requirements

Functional Requirements
  1. Test Coverage: Achieve and maintain a codebase coverage of >80%, prioritizing critical paths such as webhook reception, DAG processing, and security features.
  2. Automated Test Execution: Leverage GitHub Actions to automate the execution of tests upon every commit and pull request.
  3. Regression Suite: Develop a regression test suite that encapsulates previously identified bugs and critical issues to prevent future regressions.
  4. Documentation: Provide comprehensive documentation on the testing framework, including guidelines for writing, running, and updating tests.
Non-Functional Requirements
  • Performance: Optimize test execution to minimize impact on CI/CD timelines.
  • Reliability: Ensure tests are deterministic to avoid flaky outcomes.
  • Security: Incorporate tests to validate the effectiveness of security features.
  • Maintainability: Design the testing framework for ease of updates and scalability.

Technical Specifications

Architecture Context

MeshHook utilizes a tech stack that includes SvelteKit/Svelte 5, Supabase, and custom workers for background processing. The testing suite must integrate across these technologies, validating both individual components and their interactions.

Implementation Approach
  1. Tool Selection:
    • Unit Testing: Jest for its robustness and community support.
    • Integration Testing: Supertest to validate API integrations.
    • E2E Testing: Cypress, for its intuitive syntax and real browser testing capabilities.
  2. Test Development:
    • Employ TDD to build tests for new and existing features.
    • Create unit tests for isolated functions and components.
    • Develop integration tests to verify component interactions and data flows.
    • Implement E2E tests to simulate user interactions and workflows.
  3. CI/CD Integration:
    • Configure GitHub Actions for automated test execution against all branches.
    • Ensure tests run on pull requests and before merges to main branches.
  4. Documentation:
    • Update the MeshHook documentation to include sections on the testing strategy and maintenance.
Data Model Changes

No direct changes to the data model are anticipated for the automated testing implementation. Any required modifications will be documented during the development phase.

API Endpoints

The testing suite will cover existing API endpoints, ensuring they meet functionality and performance standards under various conditions.

Acceptance Criteria

  • Automated testing suite achieves >80% codebase coverage.
  • All tests pass consistently across local and CI/CD environments.
  • GitHub Actions are configured to run the test suite for all relevant triggers.
  • Testing documentation is complete, detailed, and accessible to the team.
  • Test suite performance benchmarks are established and met, not exceeding predetermined thresholds for CI/CD delays.

Dependencies and Prerequisites

  • Access to MeshHook's code repository and CI/CD configurations.
  • Selection and setup of testing tools compatible with the MeshHook stack.
  • Current documentation on MeshHook's architecture, coding standards, and security protocols.

Implementation Notes

Development Guidelines
  • Follow MeshHook's established coding and documentation standards.
  • Prioritize coverage for critical functionalities and paths.
  • Ensure test determinism to minimize flakiness.
Testing Strategy
  • Unit Tests: Target functions and components with mocked dependencies.
  • Integration Tests: Focus on the interactions between components and the database.
  • E2E Tests: Simulate user scenarios from start to finish, including UI interactions.
Security Considerations
  • Explicitly test security mechanisms such as RLS rules, webhook signature verification, and data sanitization.
Monitoring and Observability

Monitor and log test executions to identify flaky tests and performance bottlenecks, providing insights for continuous improvement.

Related Documentation

  • MeshHook PRD, Architecture, and Security Guidelines.
  • GitHub Actions documentation for CI/CD.
  • Testing framework documentation (Jest, Supertest, Cypress).

This PRD was AI-generated using gpt-4-turbo-preview from GitHub issue #206
Generated: 2025-10-10

📎 Generated Documentation

Diagram


This issue body was auto-generated from the PRD. Original issue content is preserved in the PRD document.
Last updated: 2025-10-10

主要言語
JavaScript
スター
6
フォーク
6
平均マージ
6分
マージ済み PR(30日)
4

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