Pitfalls to Avoid with Integration, End-to-End and Regression Tests

Over-Testing and Under-Testing Components

Inexperienced developers may either test too many details in integration and E2E tests or focus too narrowly, missing key interactions. Over-testing occurs when developers try to cover every small detail in high-level tests, leading to redundant or overly complex tests. This slows down test execution and creates maintenance overhead. Conversely, under-testing leaves gaps, especially in critical workflows where interactions matter most. Focusing on key interactions and core user paths is a better approach, balancing coverage with simplicity.
Relying on Real External Services for Integration Tests

New developers sometimes use live services for integration tests, thinking this is closer to “real-world” testing. However, real external services can be unreliable, slow, or expensive to access during testing. This setup increases test execution time and makes tests prone to failures from issues beyond the developer’s control (e.g., network problems, rate limits). Using mocks, stubs, or a dedicated test environment for external dependencies can make tests faster, more reliable, and less expensive to run.
Writing Fragile E2E Tests That Break with Minor UI Changes

E2E tests are often vulnerable to small changes in the UI, such as updates to element IDs, layout adjustments, or button text changes. Novice developers sometimes write tests that depend heavily on specific UI selectors or hardcoded text, which leads to frequent failures when the UI is updated. Writing robust E2E tests that rely on stable element attributes, such as data attributes, and using reusable page objects or helper functions can reduce this fragility.
Creating Long, Complex Test Flows in E2E Tests

Trying to cover multiple workflows in a single E2E test is a common mistake. Long, complex tests are harder to debug and often fail without providing clear information on the issue. For instance, a single test that covers user registration, login, and profile updates is complex and prone to multiple points of failure. Breaking down tests into smaller, focused scenarios (e.g., separate tests for registration and login) makes them easier to maintain and debug, and improves the clarity of test results.
Neglecting Test Maintenance in Regression Testing

Regression test suites can become large and unwieldy over time. Inexperienced developers may assume that once a regression test is written, it never needs to be revisited. However, as the codebase evolves, certain tests may become outdated, redundant, or irrelevant, leading to increased execution time and noise in test results. Regularly reviewing and updating the regression test suite—removing or updating obsolete tests—keeps it efficient and focused on relevant functionality.
Ignoring Test Data Isolation and Reusability

When tests share data (e.g., using the same user account for multiple tests) or don’t clean up after themselves, they can create conflicts, especially in integration and E2E tests. This can lead to intermittent failures or data corruption, making test results unreliable. Each test should ideally run independently with isolated data. Using unique test data, setting up and tearing down test data between runs, or working with database transactions that rollback data are best practices to maintain test isolation.
Assuming Automated Regression Testing Catches Everything

Relying solely on automated regression tests to catch all bugs is another common misconception. While regression tests are critical, they cannot cover every possible scenario or interaction. Inexperienced developers may not realise that manual exploratory testing, code reviews, and integration tests are also necessary to uncover edge cases and complex interactions that automated tests might miss.
Not Addressing Flaky Tests Promptly

Flaky tests—tests that sometimes pass and sometimes fail without code changes—are common in E2E and integration testing. Novice developers might ignore these, leading to a lack of trust in the test suite. Flaky tests can arise from timing issues, network delays, or dependencies on external services. Addressing flakiness by adding wait conditions, improving test data stability, or mocking unpredictable dependencies is essential to maintaining a reliable test suite.
Skipping CI/CD Integration for Automated Tests

Many inexperienced developers run tests manually, which can lead to inconsistent testing and missed regressions. Failing to integrate tests into a Continuous Integration/Continuous Deployment (CI/CD) pipeline means tests may not run automatically with every code push, increasing the risk of undetected issues. Setting up automated test runs in the CI/CD pipeline (e.g., using GitHub Actions or Jenkins) ensures that tests are consistently run and issues are detected early.
Writing Tests That Are Dependent on Specific Environments

Tests that work only in specific environments (e.g., tests that rely on local paths, specific databases, or custom environment variables) are difficult to scale and automate. Novice developers may write tests that pass only in the local environment but fail in staging or CI environments. Writing environment-agnostic tests by using environment variables, configuring paths dynamically, and avoiding hardcoded dependencies makes tests more portable and reliable across different stages of deployment.