Before shipping code to production, most teams ask themselves this: Are we testing the right way? This is not about coverage or tools, but it’s about choosing the testing approach that best fits the job. That’s where the debate between end-to-end (E2E) testing and unit testing begins. They might share the same end goal, but how they reach the end goal is different.
If you’ve been wondering whether you should write more unit tests or invest in full-stack E2E automation, this blog might help you. Let's break this in simple. No jargon. Clear insights from real-world experience.
What is End-to-End Testing?
End-to-end testing is about walking in the user’s shoes. You test the full journey, from opening the app to completing a task. You click, submit, and scroll, just as a user would. Instead of verifying a single function, you're checking if everything works when everything is connected.
Key Characteristics of E2E Testing
End-to-end tests reveal how your system behaves when everything comes together in real-world scenarios. Here are the deeper truths teams uncover through E2E testing:
E2E tests surface the kind of system-level issues that only emerge under full-stack, real-environment conditions. Here’s what they reveal:
Undocumented interface dependencies: These tests uncover hidden dependencies where frontend components rely on backend fields or logic not covered in the OpenAPI spec, leading to silent failures after backend refactors.
Fragile UI interactions: A harmless-looking document object model (DOM) change, like nesting a button differently or renaming a class, can break test selectors and workflows. E2E tests expose how brittle your interface bindings are.
Shared state issues in tests: When session tokens, local storage, or cookies aren’t properly isolated, they cause cascading test failures. These only show up when test flows are executed in sequence.
Logical dead ends in UX: The backend works perfectly fine, the UI shows no error, but the user can’t complete the flow. E2E tests detect these black hole experiences.
Overconfidence in mocked services: Simulated responses don’t include real-world edge cases, timeouts, malformed payloads, or partial failures. E2E runs highlight these gaps.
Types of E2E Testing
Now that you know what E2E tests reveal, let’s break down the different types of E2E tests you can use depending on your system goals and release maturity.
Smoke Testing: Validates core system readiness after a deployment. It checks whether critical services boot up, endpoints are responsive, and primary workflows (like authentication or homepage load) don’t throw fatal errors.
Regression Testing: Replays previously working user flows, like form submissions or permission toggles, after a code change to detect functionality drift caused by new commits.
UI-driven Automation: Simulates real user interactions with scripts that click, scroll, drag, and enter inputs in the browser. Great for testing UX-heavy features such as wizards, file uploads, or drag-and-drop components.
Cross-browser and Cross-device Testing: Runs the same test suite on different environments, Safari on iOS, Firefox on Windows, and Chrome on Android, to expose layout mismatches, inconsistent rendering, or input handling bugs.
Critical Path Testing: Targets high-value, high-risk workflows like user onboarding, subscription upgrades, or multi-step transactions. If these break, revenue or user trust is directly affected.
Data-driven Testing: Runs the same flow with varying data inputs to simulate different user profiles or edge cases, e.g., empty vs. populated cart, valid vs. expired promo codes, or malformed input formats.
Visual Regression Testing: Captures snapshots of your UI and compares them across versions. It flags any unintended visual drift, like button misalignment, font shifts, or color inconsistencies that might impact the user experience.
Pros and Cons of E2E Testing
While E2E testing offers powerful validation across the entire stack, it comes with trade-offs. Here’s a breakdown of what you gain and what you need to watch out for.
Pros:
Full-stack integrity: Validates system cohesion across UI, backend APIs, databases, auth services, and third-party integrations
Contract and schema validation: Surfaces misalignments between frontend expectations and backend API responses that static typing can't detect
Interaction realism: Tests replicate browser-driven input events, real key presses, DOM interactions, and timing behaviors, not just function calls
Protection against silent regressions: Detects failures where no errors are thrown, but user journeys break due to subtle logic or UI changes.
CI/CD gatekeeping: Acts as a quality barrier in CI pipelines, ensuring deploys only proceed when critical workflows function as intended.
Cons:
Slow execution time: Browser-based automation, dynamic environment provisioning, and end-to-end cross-layer validations contribute to increased test latency and extended feedback loops compared to isolated unit or integration tests
High flakiness: Tests are prone to failure due to DOM changes, async race conditions, or third-party instability, even if core logic is fine
Opaque debugging paths: Failures often require digging through logs, inspecting network traces, and correlating frontend traces with backend errors.
Test brittleness: Minor UI refactors, changing element order or class names, can break selectors and require test maintenance
Resource-intensive: Parallel test execution is costly, test data setup is complex, and environment parity between local and CI is non-trivial
Real-world example scenario
In 2016, a global retail company launched an updated version of its e-commerce platform just before Black Friday. The checkout flow, redesigned for mobile responsiveness, worked flawlessly in isolation during functional tests. But on the day of the launch, 32% of orders failed at the payment stage.
What went wrong?
The team had updated the authentication mechanism between the payment gateway and the inventory system, but it wasn't tested in an end-to-end context.
The oversight?
No one had validated the complete transaction flow. The issue was not with the individual components, but with their orchestration.
The impact?
32% of orders failed silently at the payment stage
Millions in revenue were lost during one of the highest traffic periods of the year
Customer support was overwhelmed with complaints
The brand's reputation took a hit on social media and in media coverage
The Highlights:
Only End-to-End testing could have caught this hidden latency issue across the stack, from frontend UI interaction to backend event queues and third-party card network propagation.
Avo Automation – Why E2E Testing Matters
What is Unit Testing?
It examines the smallest parts of your code, functions, methods, and components in isolation. It’s more about logic than flow. No UI. No external systems. Just code.
Key Characteristics of Unit Testing
Let’s first outline what makes unit tests a cornerstone of developer-driven testing:
Works with isolated units of code: Unit tests run independently of any external service or system
Fast execution: Since they only evaluate small pieces of logic, they complete in milliseconds
Code-level test cases: This helps detect regressions during active code development
Highly maintainable when properly scoped: Well-isolated tests remain stable and unaffected by unrelated code changes.
Types of E2E Testing
Just like E2E testing covers full user journeys, unit testing breaks down into different types based on the kind of logic it’s meant to validate. Here’s how each type serves a purpose in building reliable, modular code.
Function Testing: Validates the correctness of individual functions in isolation. For instance, testing whether a calculateDiscount(100, 20) returns 80. These are simple to write and act as the first line of defence against bugs in logic
Class Testing: Focuses on testing class methods and their effect on internal state. For example, you may test a User.promoteToAdmin() method to ensure it correctly changes the user’s role from "guest" to "admin". Class tests ensure behavior consistency in object-oriented code
Branch Testing: Verifies logic paths triggered by conditionals such as if-else, switch-case, or ternary operators. Suppose a function returns different shipping costs based on the destination branch. Testing ensures each condition is exercised
Error-handling Tests: Tests how the system behaves with invalid, null, or unexpected inputs. For example, passing undefined to a JSON parser should throw an error gracefully. These tests simulate edge cases and ensure your code fails safely, not catastrophically
Pros and Cons of Unit Testing
Before adopting unit testing extensively, it’s important to understand its strengths and limitations.
Pros:
Fast Execution: Unit tests run in milliseconds, making them ideal for frequent checks during development
Early Bug Detection: Since they test isolated units, it’s easy to detect and fix issues close to where they originate
High Maintainability: Unit tests are easy to maintain and adapt as code evolves
Developer Ownership: These tests are typically created alongside the code, promoting accountability and enabling faster development cycles
Cons:
Limited Scope: Unit tests only validate isolated logic; they don’t ensure that integrated systems work well together
False Sense of Security: All unit tests may pass even when the application breaks in real scenarios due to integration failures
Requires Discipline: Poorly written or overly broad unit tests can become brittle and hard to maintain.
Real-world example snippet
Let’s look at a real-world example to understand what a unit test looks like in action.
This test checks just one function, calculateTotal, without relying on any database, UI, or network call. That's exactly what a unit test is meant to do: test one unit of logic in isolation.
Key Differences Between Unit Testing and End-to-End Testing
While both are crucial pillars of a complete test strategy. Below are some key differences to help you decide where each should be applied.
1. What You’re Testing
Unit Testing: Tests one small piece of code, like a function or method
E2E Testing: Tests the entire user journey, from clicking a button to getting a confirmation email
2. How It Runs
Unit Testing: Runs fast and doesn’t need a full app or server running
E2E Testing: Runs on the full system with UI, APIs, and databases active
3. Use of Fake Data
Unit Testing: Uses fake functions or dummy data to test logic
E2E Testing: Uses real systems or near-real setups to test actual flows
4. What It Can Detect
Unit Testing: Detects bugs in calculations or logic
E2E Testing: Detects issues when systems are not in sync with each other properly
5. When It’s Useful
Unit Testing: Great for quickly checking new code works before pushing
E2E Testing: Best before a big launch or feature release to check everything works together
When to Use Unit Testing vs E2E Testing
Knowing when to rely on unit testing versus end-to-end (E2E) testing can make or break your quality strategy. Here’s a quick guide to help you decide which to use depending on the situation:
Choose Unit Testing When | Choose E2E Testing When |
When you want instant checks while writing code | When you can afford slower tests that run post-merge or pre-release |
Ideal when editing backend logic, utilities, or data models | Not useful, there’s no visible change to test |
You already trust the logic and want to ensure stability at the lowest level | You need to simulate real user actions and flows at scale |
When you use mocks or simulate the API response | When you want to test actual integration, only when real responses matter |
When you want to verify that internal logic didn’t break due to refactoring | When you want to confirm that the entire user journey still works |
Breakpoints and stack traces point you directly to the issue | You need to investigate across systems (UI, API, DB) to pinpoint the failure |
Helpful only if the issue is with internal logic | Crucial if the user reports a broken experience end-to-end |
Unit Testing and E2E Testing in Agile and DevOps
In Agile and DevOps teams, testing isn’t something that happens at the end. It happens while the software is being built, and both unit tests and E2E tests play important roles.
Unit testing fits perfectly in Agile because it helps developers quickly check if small pieces of code work correctly as they build. It’s fast, easy to run often, and detects bugs early.
E2E testing works well with DevOps because it checks if the whole system works from a user’s point of view. These tests often run automatically after code is deployed, helping teams detect any breakage before users face it.
Common Mistakes to Avoid
When teams depend too much on only one kind of test, either just unit tests or only end-to-end (E2E) tests, they miss important bugs and risk delays or failures later.
Why is this a mistake?
Unit tests check if small pieces of code work, but they don’t show if those pieces work well together. E2E tests check full user journeys, but they can miss bugs hidden deep in the code and are slow to run.
What to do instead:
Follow the test pyramid:
Write unit tests
Few Integration tests
Only a small number of E2E tests
This way, you cover more ground and keep your test suite fast and reliable.
Not Updating Tests with Changing Code
When the code changes but tests are not updated, those tests can become useless.
Why is this a mistake?
If tests aren’t updated, they might pass even when the code is broken or fail for no reason. This can confuse the team and hide real problems.
What to do instead:
Whenever you change code, like during a feature update or bug fix, review and update the related tests too. Make it a regular part of your code review or merge process.
Over-testing with E2E
E2E tests are essential, but relying too heavily on them and not performing other types of tests in the tester's cycle can lead to a lack of visibility into hidden bugs that unit and regression tests can reveal.
Why is this a mistake?
Slow feedback: E2E tests take time to run, which delays releases
Flaky results: These tests often fail for reasons like internet issues or test environment bugs, not actual code problems
Hard to debug: It’s tough to figure out why an E2E test failed, especially if it’s testing too many things at once
What to do instead:
Use E2E tests only for the most important user flow or at the end of the release or pre-release. For other checks, use faster unit or integration tests.
Conclusion: Choosing the Right Testing Strategy with Supatest AI
Unit and E2E tests aren’t competing tools, they’re part of the same toolbox. The goal isn’t to write the most tests; it’s to write the right ones that give you fast, reliable feedback.
Treat your tests like working code: keep them clean, update them with changes, and don’t overload them with things they’re not meant to do.
Testing well isn’t about coverage numbers. It’s about confidence in your releases, in your refactors, and in your ability to move fast without breaking things.
FAQs related to E2E vs Unit Testing
What is the main difference between unit testing and E2E testing?
Unit tests check small, isolated parts of your code, like individual functions or components.
E2E (end-to-end) tests check if a whole flow works, like a user logging in or placing an order.
Is unit testing faster than end-to-end testing?
Yes, much faster.
Unit tests run in milliseconds because they don’t rely on the browser or network.
E2E tests take longer since they simulate real user actions across the full app.
Can I replace unit testing with E2E tests?
Not a good idea.
E2E tests are slower, harder to maintain, and not great for catching logic bugs.
You need unit tests for fast feedback and code-level coverage, E2E is for high-level workflows.
How many unit vs E2E tests should I write?
Follow the testing pyramid:
Most tests should be unit tests
Some should be integration tests
A few should be E2E tests
This keeps your test suite fast, reliable, and easy to maintain.
Which is better for performance testing: E2E or unit?
Neither is ideal for deep performance testing.
But if you want to test how a full user flow performs under load, E2E is better.
For micro-optimizations (like a slow function), profiling tools work better than unit tests.
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