Testing App To Perfection

Introduction

Each time we successfully implement a new feature or functional change in the application, we immediately follow up with real user testing.

• The most direct and efficient approach is manual testing.
• For example, using browser developer tools, we can verify whether the service worker is correctly registered and running, ensure that dynamic content is being properly cached in Cache Storage, and confirm that IndexedDB is populated with the expected entries. After this verification, we simulate offline conditions by disabling Wi-Fi or enabling "Offline" mode in the network settings to verify offline functionality of a PWA.
• We also review console logs for any reported errors, trace the execution flow, and ensure that key functions are invoked as expected.
• Performance metrics are assessed using Lighthouse, which is integrated into Chrome DevTools.
• When everything runs smoothly on our own devices, the satisfaction is incredibly rewarding.

Functional Tests

When an app is relatively simple, manual testing is often sufficient and manageable to ensure all features works as expected.

• However, as the application grows in complexity, relying solely on manual testing becomes increasingly unreliable.
• New implementations may inadvertently break existing functionality that previously worked.

In large-scale or enterprise development, teams that are serious about delivering reliable software adopt automated testing as an industry standard and best practice.

• This typically involves structured approaches such as the testing pyramid or testing trophy, which balance unit tests, integration tests and end-to-end (E2E) tests to detect bugs early, accelerate development cycles and improve code quality.

Beyond built-in tools like npm audit (for checking dependency vulnerabilities) and Next.js's optimized build process (for performance, bundling and deployment efficiency), automated tests are essentially code written by developers to validate that other code behaves as expected.

• These tests live within the main codebase and are executed repeatedly and automatically, typically before each commit, on every push, or as part of the CI/CD pipeline.

Despite rigorous automated testing, edge cases can still arise.

• In production, real-world usage may uncover issues not visible in a controlled staging environment due to unpredictable variables, such as network conditions, device models, screen sizes, browser versions, or user behaviour.

In reality, constraints such as tight deadlines, limited resources or budget limitations, can lead to reduced test coverage.

• As a result, teams typically prioritize testing for the most critical features and high-risk areas to maximize impact.

Performance Tests

Even if an application works flawlessly for a few users (as confirmed through functional testing), it may behave very differently under high user load.

Load testing

• Simulates many "virtual users" accessing the system simultaneously to evaluate whether it can handle the expected number of concurrent users and transactions while staying within acceptable performance thresholds.
• It helps assess system behaviour under normal or peak usage conditions.

Stress testing

• Goes further by pushing the application beyond its normal operational limits to identify its breaking point and observe how it degrades or recovers under extreme pressure.

Scalability testing

• Often combined with load and stress testing, this evaluates whether the system can effectively scale to accommodate a growing user base or increasing data volume while maintaining performance.
• It also verifies whether adding resources (such as additional servers or containers) actually improves performance under heavier loads.

Summary

Testing is not an unnecessary chore; it is s a critical part of delivering stable software.

• However, for personal or simple projects, the risk of critical bugs is often low, and the cost of fixing issues is minimal.
• In such cases, implementing comprehensive automated tests may be overkill, as they can be resource-intensive without providing proportional value.
• However, for commercial or production-level projects, gradual adoption of automated tests is highly recommended.