Refining Testing Strategies and PR Workflows for Scalable Development

Introduction The Case for Comprehensive Testing A Pragmatic Approach to Testing A Breakdown of Our Testing Strategy 1. End-to-End (E2E) Testing 2. Unit Testing 3. Visual Regression Testing The Cost of Quality Assurance PR Workflow: The Foundation of Code Quality Building a Smarter PR Pipeline Optimized Branch Management for Scalable Development Feature Branch Workflow Smart Test Execution Using Change Detection Final Thoughts

Introduction

Building a reliable software platform requires more than just writing code—it demands a structured approach to testing and a well-thought-out PR workflow. Without these, projects can quickly become unmanageable, riddled with bugs, and burdened with security risks.

Imagine launching a new feature, only to find it breaking key functionality in production. Now imagine the chaos of scrambling to fix it post-release. A robust testing strategy prevents these scenarios, ensuring that every deployment is stable, scalable, and secure.

In this post, we explore how a carefully planned test suite and a structured PR workflow can help developers maintain high-quality code while optimizing costs.

The Case for Comprehensive Testing

Testing is often seen as an overhead expense, but in reality, it’s an investment in long-term stability. The key is not just to test but to test smartly—balancing coverage, cost, and execution time.

A Pragmatic Approach to Testing

A pragmatic testing approach recognizes that not all tests are equally valuable or necessary in every scenario. The key is prioritizing tests based on their impact and likelihood of catching critical bugs. This involves a multi-layered approach:

Testing at Different Levels:

Each level of testing serves a distinct purpose, from catching regressions in the UI to validating individual functions.

Instead of running every test in every pipeline execution, we optimize when and how different test types are executed.

Balancing Speed and Depth:

Running a full E2E suite on every commit would be inefficient, slowing down the development cycle.

Instead, lightweight unit tests run automatically on every PR, while deeper E2E and visual tests run only on staging environments.

Parallelizing Tests for Efficiency:

We split tests across multiple environments and execute them in parallel to minimize feedback time.

For example, web and mobile E2E tests run in separate environments to avoid bottlenecks.

Focusing on Critical Path Coverage:

Prioritizing test coverage for core user flows ensures that the most important functionalities remain stable.

Tests should focus on areas prone to frequent changes, such as authentication, payments, and critical UI elements.

Using Change Detection to Run Relevant Tests:

Instead of running all tests on every update, we use Git’s diffing capabilities to identify affected areas.

For instance, if only the dashboard component is modified, we trigger Cypress and unit tests specific to that component.

Preventing Flaky Tests from Blocking Deployments:

Flaky tests can create frustration and erode confidence in the test suite.

We implement retry mechanisms and quarantine unstable tests until they are fixed.

A Breakdown of Our Testing Strategy

1. End-to-End (E2E) Testing

E2E tests simulate real user interactions, ensuring that core workflows function as expected. Given their complexity, they tend to be expensive but are invaluable for catching regressions.

Web: Cypress ($75/month) provides a robust UI testing framework.

Mobile: Maestro ($250/month) offers a streamlined mobile automation solution.

2. Unit Testing

At the heart of any test suite, unit tests validate individual components and functions. These are relatively low-cost but crucial in maintaining core logic.

API: Jest (~$25/month) efficiently tests backend logic.

Mobile: React Native Testing Library (~$25/month) ensures mobile UI integrity.

Web: React Testing Library (~$25/month) validates frontend behavior.

3. Visual Regression Testing

A visually appealing app can break with even a minor CSS update. Visual regression testing ensures UI consistency across updates.

Web: Chromatic ($150/month) detects unintended UI changes.

Mobile: Sherlo ($150/month) offers mobile-focused visual testing.

The Cost of Quality Assurance

Balancing test coverage and cost is essential:

Full test coverage (E2E, unit, visual): $700/month ($8,400/year)

Partial test coverage (excluding visual): $350/month ($3,900/year)

While it may seem expensive, these costs pale in comparison to the potential fallout of undetected critical issues in production.

PR Workflow: The Foundation of Code Quality

A well-structured PR workflow is like a security checkpoint—it ensures that only high-quality, secure, and maintainable code reaches production. Without it, issues can slip through, leading to technical debt and instability.

Building a Smarter PR Pipeline

To maintain high standards, each PR must go through the following checks:

Linting – Ensuring consistency in code style and preventing common mistakes.

Security Scans – Catching vulnerabilities before they reach production.

Code Quality Checks – Maintaining a maintainable and efficient codebase.

Automated LLM-Powered PR Comments – Leveraging AI to provide insightful feedback on changes.

Review & Approvals – Enforcing peer reviews to uphold quality standards.

Optimized Branch Management for Scalable Development

An organized branching strategy is crucial for maintaining workflow efficiency. Without clear structure, teams risk merging unstable features, delaying releases, or encountering complex conflicts.

We implement a hierarchical Git branching model to ensure smooth development and deployment:

Feature Branch Workflow

Each feature branch follows a strict validation process before integration:

Develop: Engineers create feature branches off development and push changes.

Test: Unit tests run automatically to catch regressions.

Stage: Once validated, the branch merges into stage, triggering E2E and visual tests.

Review & Approve: The code undergoes peer review for quality assurance.

Deploy: Upon approval, the changes merge into main and roll out to production.

                ┌───────────┐
                │   Main    │  <-- Production-ready branch
                └────▲──────┘
                     │
               ┌─────┴─────┐
               │  Stage    │  <-- Pre-production validation branch
               └─────▲─────┘
                     │
      ┌──────────┬───┴────┬──────────┐
      │          │        │          │
┌─────┴─────┐ ┌──┴────┐ ┌─┴─────┐ ┌──┴─────┐
│  Feature  │ │Feature│ │Feature│ │Feature │  <-- Feature branches for new development
└────▲──────┘ └─▲────▲┘ └───▲───┘ └──▲─────┘
     │          │    │      │        │
     │          │    │      │        │
     │          │    │      │        │
┌────┴──────────┴────┴──────┴─────────┐
│           Development               │  <-- Rapid iterations, hotfixes, and experiments
└─────────────────────────────────────┘

Smart Test Execution Using Change Detection

Rather than running all tests on every commit, we leverage Git’s diff command to selectively trigger relevant test suites:

git diff --name-only main feature-branch -- app        # Run Maestro & unit tests
git diff --name-only main feature-branch -- shared     # Trigger all tests
git diff --name-only main feature-branch -- dashboard  # Run Cypress & unit tests
git diff --name-only main feature-branch -- widget     # Run Cypress & unit tests

By running only necessary tests, we optimize CI/CD performance, reducing execution time and cloud compute costs.

Final Thoughts

Building scalable software isn’t just about writing good code—it’s about testing smartly and maintaining a structured PR workflow. By striking the right balance between test coverage and cost, while implementing an efficient branching strategy, we can ensure that our platform remains robust, secure, and adaptable as it grows.

The real question is: Are you ready to take your development process to the next level?