Best Practices for Designing a Test Automation Framework

Govinda Solanki
9 min readSep 28, 2024

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Image credit: DALL-E

1. Keep it Simple (KISS Principle)

Your automation framework should be simple and easy to understand.

  • Break down complex tests into smaller, reusable modules. This makes it easier to understand, maintain, and reuse code snippets.
  • Choose meaningful names for test cases, methods, and variables.
  • Avoid Over-Engineering. Don’t add unnecessary complexity, like extra design patterns or abstractions, unless they solve an immediate problem.

Over-Engineering Example: Using a Singleton Pattern for WebDriver adds unnecessary complexity. It can create issues when you need to run tests in parallel, as each test will share the same WebDriver instance.

Static keyword in testing can block parallel test execution. When you use static objects (especially mutable ones like WebDriver), it means tests can’t run simultaneously because they’re sharing the same resource. This prevents concurrent testing and slows down your test suite. To enable parallel testing, avoid static objects and ensure each test can run independently without interfering with others.

2. Modular Approach

A test automation framework should follow a modular approach where components are loosely coupled, and changes in one part of the framework do not affect others. This means having separate modules for test data, utility methods, page objects, and test execution.

Example:

  • Create a module for Test Data Handling: Place all your test data in external files like JSON or XML.
  • Create a module for Utilities: Common functions like reading from JSON files or taking screenshots can go here.
  • Create a module for Test Cases: All your test cases will reside here, possibly written using TestNG annotations.
  • Use the Page Object Model for UI Automation: POM separates test logic from page structure. Each web page is represented by a Java class with web elements as variables and methods to interact with them. This simplifies maintenance when the UI changes.

3. Manage Test Data and Preconditions via API or DB

When performing UI automation, it’s best to handle test data setup and preconditions through API or DB rather than through the UI itself. UI test cases tend to be more fragile compared to API or DB-driven tests. Setting up test data via API or DB is much faster than navigating through the UI, reducing overall test execution time. By separating data setup, the UI test can focus on what it’s meant to test: the user interface. This leads to more focused and accurate testing.

4. Avoid Excel in a Test Automation Framework

Avoid using Excel for managing test data in automation frameworks for several reasons.

  1. Version Control and Collaboration Issues
    Excel files are hard to manage in version control systems like Git, making collaboration difficult.
  2. Performance Issues
    Excel is slower to read and write compared to formats like JSON, XML, or databases, slowing down test execution.
  3. Data Integrity
    Excel files can be easily corrupted or misformatted, leading to failed tests. Text-based formats are more reliable.
  4. Not Ideal for Complex Data
    Handling complex data structures in Excel is difficult. JSON and XML are better suited for this.
  5. Limited Automation Support
    Manipulating Excel requires additional libraries, adding complexity and dependencies to the framework.
  6. Difficulty in Continuous Integration
    Integrating Excel-based tests into CI/CD pipelines is more challenging than using code-based frameworks.

Using alternatives like JSON, XML, databases, or CSVs makes your automation framework faster, easier to manage, and more robust.

5. Use Design Patterns

Design patterns can improve the structure and maintainability of your framework.

Factory Pattern:
The Factory Design Pattern is a way to create objects in a flexible and reusable manner. Imagine you have a super class with multiple subclasses, and based on some input, you need to return an instance of a particular subclass. The Factory Design Pattern helps you achieve this by using a factory class to handle the creation of these objects.

  1. Super Class and Subclasses: You have a super class (e.g., Driver) and multiple subclasses (e.g., AndroidDriver and IOSDriver).
  2. Factory Class: A factory class (e.g., DriverFactory) is responsible for creating instances of these subclasses based on some input (e.g., platform type).

Strategy Pattern:
The Strategy Design Pattern is a behavioral design pattern that allows you to define a family of algorithms, encapsulate each one as a separate class, and make them interchangeable. This pattern lets the algorithm vary independently from the clients that use it.

You are working on an automation framework that needs to support different types of browsers for testing. Instead of writing separate code for each browser, you can use the Strategy Pattern to define different browser strategies and switch between them easily.

Builder Pattern: Helps build complex objects step by step.

Design Patterns In Java With Examples You tube playlist.

6. Use Static Code Analysis Tools like SonarLint

Tools like SonarLint help detect potential issues in your code such as bugs, code smells, or security vulnerabilities.

Example: SonarLint can highlight issues like unused variables or functions, which helps maintain clean and efficient code. It integrates directly with your IDE and provides real-time feedback as you write code.

7. Data-Driven Testing

Using a data-driven approach allows you to run the same test script with multiple sets of data. This improves reusability and ensures wider test coverage with less effort.

8. Exception Handling and Logging

Proper exception handling and logging are crucial for understanding test failures. Every action in the framework should be logged, and test failures should throw meaningful exceptions.

9. Identify Tests to Automate

Focus on predictable, repetitive, and critical tests that enhance efficiency and accuracy. The goal should be to identify the tests that are good candidates for automation, rather than trying to automate every possible test.

  • Choose tests that are executed frequently.
  • For UI Automation, try to automate tests that cover the most critical paths for your business.
  • Create standalone tests that can run in any order or in parallel, which helps improve test suite performance, reliability, and makes debugging easier.
  • Each test should set up its own preconditions and clean up after itself, ensuring a clean state for the next test.
  • It is crucial that each test is independent and does not rely on the outcome of previous tests.

10. Wait Utility for UI Automation

  • Avoid Hard Coded Wait
    Avoid using hard-coded waits like Thread.sleep(), as they can make tests slow and unreliable.
  • Centralize Wait Logic
    Create a dedicated wait utility class to encapsulate all waiting logic, making it easier to maintain and update.
  • Use Explicit Waits Instead of Implicit Waits
    Focuses on waiting for specific conditions to be met, such as an element being clickable or visible.
  • Parameterize Timeout Values
    Allow customizable timeout values for different scenarios, with sensible defaults.
  • Time Out Strategy
    Set realistic timeouts to avoid long delays. Choose a balance that ensures elements load but doesn’t make tests slow. Overusing waits (even explicit ones) can make tests sluggish. Wait only for necessary conditions and optimize polling intervals

11. POJO Classes for API Automation

Using POJO (Plain Old Java Object) classes in API automation has several benefits. While some teams may skip POJO classes for simplicity, there are strong reasons to use them.

  • Strong Typing and Compile-Time Safety
    POJO classes provide strong typing, which ensures that the data you’re working with has a well-defined structure. Compile-time errors can catch issues earlier, such as type mismatches or missing fields, reducing runtime errors that could occur if you’re directly working with JSON.
  • Code Readability and Maintainability
    When using POJOs, the structure of your data is explicit, making the code more readable and easier to maintain.
    This avoids the need to navigate nested maps or JSON strings to extract fields, which can become error-prone and less readable for complex APIs.
  • Easier Refactoring
    When API responses change, you only need to update the POJO class, not multiple places in the code.
  • Validation of the Full Response
    POJO classes can be used to automatically map and validate the entire API response. Tools like Jackson or Gson allow for JSON-to-object conversion with validation of field types.
    This prevents partial validation issues where some fields might be missed if you’re manually checking the JSON structure.

In the long run, using POJOs in API automation is a more scalable, maintainable, and robust approach. While it might introduce some initial overhead in terms of creating the POJO classes, the benefits in terms of readability, test structure, type safety, and flexibility far outweigh the effort. Skipping POJOs might work in certain cases, but for complex applications with evolving APIs, POJOs offer better control and reduce the chances of flaky or fragile tests.

12. Follow DRY Principle (Don’t Repeat Yourself)

  • Avoid Duplication in Locators (XPath)
    Centralize locators in a Page Object Class rather than duplicating them across multiple test cases.
  • Use Inheritance Wisely
    In cases where common functionality is required across different tests, inheritance can help share the same methods. However, be mindful of overusing inheritance, as it can lead to tight coupling.
  • Reusable Test Setup and Teardown
    Use a Base Test Class to set up and tear down the environment in one place instead of repeating the setup logic in every test.
    Identify common test steps that are repeated across multiple test cases and extract them into reusable methods or functions.

13. Independent Test

Independent tests not only enable parallel execution but also make maintenance easier. While it may not always be possible to achieve complete independence, it is considered a best practice to design test cases that can run on their own. This approach improves reliability, reduces dependencies, and allows for faster, more efficient testing.

14. Avoid Hardcoding — Use Config Files

Store URLs, credentials, and other data in configuration files rather than hardcoding them.

15. Adhere to SOLID Principles

Following SOLID principles improves code maintainability and flexibility.

16. Regular Review and Refactoring

  • Periodically review and update your test automation framework: This ensures that it remains effective and adaptable to changing requirements.
  • Identify areas for improvement: Look for opportunities to optimize performance, enhance maintainability, or increase test coverage.
  • Updating outdated libraries and tools: Keep your framework updated with the latest technologies.
  • Removing redundant or unnecessary code: Streamline your test scripts for better efficiency.
  • Improving test coverage: Ensure that your tests thoroughly cover all relevant scenarios.

17 . Reporting

Your report should be customizable. Not all projects need the same level of detail, so a report should allow configuration to show/hide sections like screenshots, logs, or environment details.

Report tests that are slow or often fail to optimize your testing process.

Include summary statistics at the top of the report to give a quick overview of the overall test execution.

18 . Cucumber — not a Test Automation Tool

Many organizations misuse Cucumber, leading to unnecessary complexity without the intended benefits of Behavior-Driven Development (BDD). Use simpler tools unless fully committing to the BDD process.

19 . Choose the Right Automation Tool

Selecting the wrong tool can hinder project success. Tools should be chosen based on specific project needs, not popularity.

20 . Use Small, Focused Tests that Check Only One Specific Feature or Component

Automated Atomic Tests (AAT) are small, focused UI tests that check single features quickly, reducing test execution time and improving reliability by breaking complex scenarios into isolated, fast-running tests that can be executed in parallel.

Advantages:

  1. Fail Fast
  2. Reduce Test Flakines, Easier maintenance
  3. Run tests in paralle, Improved Performance
  4. Dramatically reduce total test execution time

21 . Test Automation Pyramid

  • Focus on unit tests at the bottom (fastest, most reliable)
  • Fewer API tests in the middle
  • Minimal UI tests at the top

22 .Keeping Your Test Data Clean

Creating and deleting test data for each test ensures that:

  1. Test Isolation: Each test runs independently without being affected by the data created by other tests.
  2. Consistency: Tests start with a known state, making them more reliable and easier to debug.
  3. Parallel Execution: Tests can be run in parallel without interfering with each other, improving test suite execution time.

23 .Data-Driven API Tests

  1. Use Realistic Data: Understand the business logic behind the API and the data it processes to create realistic test scenarios.
  2. Use Data to Drive Dynamic Assertions: Avoid hard-coding expected outcomes. Instead, use dynamic assertions that adapt to different test scenarios, making your tests more flexible and easier to maintain.
  3. Track API Responses: Record and store API responses to maintain a history of test results. This helps in identifying when and where issues were introduced, making debugging easier.
  4. Repurpose Data-Driven Functional Tests for Performance and Security: Reuse your data-driven functional tests for performance and security testing. This adds realism to these tests and maximizes the value of your initial investment in setting up data-driven tests.

These are just guidelines, adapt them to fit your organization’s specific needs.

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