How do you build an automation framework?

Building an automation framework starts with selecting the right tools and technologies that align with your project's tech stack and team expertise. Design a modular structure, incorporating reusable components for test scripts, data handling, and reporting. Implement best practices like keyword-driven, data-driven, or hybrid approaches to ensure flexibility and scalability. Finally, integrate the framework with your CI/CD pipeline for continuous testing and quick feedback, and continuously refine it based on feedback and metrics to enhance its effectiveness.

For scope I suggest picking up the complex test case so that almost all the complicated web elements are covered (like frames or if the element has overlay). By this we can be sure that rest of the test scenarios can be automated

First of all, the proof of concept (POC) is important before starting or building any automation framework, That gives the confidence and provides the feasibility of how the automation framework helps in reducing manual effort, how much % automation coverage can be done and if the framework development actually benefits the ROI and also to understand the complexity areas of automation as early to strategize a best automation framework layout.

No matter what and how we are going to automate, first of all we need to build an automation environment that integrates our future framework with existing processes. Our repos and pipelines should be integrated into existing CI/CD and reports should be connected with team messengers. If we don't have clear processes and don't get instant reports on our automated tests, then it doesn't have any meaning in such automation. So, here is the strategy: 1. Environment first 2. Only then languages, tools, frameworks and tests

It took me 7 years to understand how to build the most suitable strategy for most cases that I solve on daily basis. When all the design patterns do not meet your requirements - create your own one :) That's how I created my own automation framework, that combines different tools in a simple wrapper. I call it Data Structured Automation Testing(DSAT) and it stores information about elements and actions in a data structure, you only need to add new actions(if needed) to the existing code, without changing it

:= Design patterns, such as the Page Object Model (POM), Keyword-Driven, and Data-Driven, offer structured solutions for automation frameworks, enhancing modularity and maintainability. := POM separates test logic from web elements, Keyword-Driven employs external keyword storage for test actions, and Data-Driven uses external data sources for test input. ;= These patterns facilitate easy maintenance, updates, and scalability, enabling efficient test case creation, modification, and execution with different datasets

In my career, I've successfully implemented several design patterns in automation frameworks, with particular success using the Page Object Model (POM). On one project, we applied POM to separate the user interface elements from the test logic, which dramatically improved the maintainability and scalability of our tests. This approach allowed non-developers to easily understand and update tests, facilitating a more collaborative environment. By further incorporating Data-Driven techniques, we enabled tests to be run with various data sets, enhancing the framework's flexibility and reducing the time needed for test preparation.

Choosing an appropriate design pattern is crucial for ensuring that the automation framework is sustainable and scalable. Patterns like the Page Object Model (POM) for UI automation or the Service Object Model for API testing help organize code and separate test logic from implementation details. These patterns promote component reuse and simplify maintenance, allowing system changes to be incorporated with less effort. The choice of design pattern should consider the project's complexity and the team's experience, ensuring that the code is clear and easy to understand.

Building an automation framework begins with selecting a suitable design pattern. Common choices include Page Object Model (POM), BDD (Behavior-Driven Development), and Modular or Hybrid frameworks. Each pattern offers distinct advantages in organizing code, enhancing maintainability, and promoting reusability. By carefully evaluating project requirements and considering factors like scalability and ease of maintenance, you can choose the most appropriate design pattern to construct a robust and efficient automation framework.

We can use dynamic locators to reduce the duplicity of code. Also the methods with same functionality and a little different inputs can be overloaded with different input parameters.

There is one important rule, that I learned during my journey in automation - abstraction is never enough. Sometimes it's really make sense to write something simple and working "here and now". But you will suffer later, when you need to scale your solution. So, before writing something "just because" - thing twice how you will maintain it later

➤Use single responsibility principle while defining your test classes. ➤Use DRY principle, specially if you're developing UI based automation and using POM as your design pattern. ➤Locator strategy should be consistent throughout the codebase i.e. dynamic locators, use id if present or css for direct elements and xpaths for more complex elements. ➤No assertions in page objects. ➤Use TestNg/Pytest for defining your execution order. ➤Basic OOPs principle like abstraction comes in pretty handy while developing automation code base. ➤Try not to use any external files for test data, unless absolutely needed, and try to store locally in the codebase.

Create a codebase that is both strong and adaptable by employing clear naming conventions, thorough documentation, and strategic use of OOP principles like abstraction, encapsulation, inheritance, and polymorphism. Incorporate robust error handling and detailed logging to facilitate debugging and ensure seamless functionality. Utilize external libraries to enhance your framework's capabilities efficiently.

Implementing a robust and flexible code base is essential to support the growth and evolution of automated tests. This involves creating a modular and reusable structure, where test components are logically organized and can be easily modified or extended. It is important to include coding practices such as version control, code reviews, and unit testing to ensure code quality. Additionally, using good programming practices, like separation of concerns and dependency injection, contributes to the flexibility and maintainability of the code base.

:= Align automation framework with specific testing goals for effective guidance. := Ensure framework's modularity for easy maintenance and scalability. := Integrate with CI/CD pipelines for rapid feedback and faster release cycles.

Integrating the automation framework with other tools and systems is an important step to maximize its effectiveness and efficiency. This may include integration with test management systems, like Jira or Azure DevOps, for tracking and documenting test cases, as well as CI/CD tools for automating build and deployment processes. Furthermore, it is beneficial to integrate with monitoring and reporting systems, which help quickly identify failures and analyze results. Seamless integration with the development and operations environment facilitates collaboration between teams and ensures that automation is an integral part of the development cycle.

I decided to divide my automation framework with something that I call environment framework. They are different services now and I use Kafka to receive reports from automation framework. Actually, everything in "environment framework" are different services now. One is used to receive reports, another to convert them for specified channel(email, slack, etc.), and another one to send them. They all are integrated into CI/CD and built using different languages and technologies like gRPC and etc.

1. Start small with integrations. First, focus on connecting with a few key tools and gradually add more integrations as needed. This allows for easier implementation and troubleshooting. 2. Clear documentation is crucial. Document your integrations thoroughly so anyone on the team can understand how the framework interacts with other tools. This will save time, reduce confusion, and make future maintenance easy.

CI/CD Pipelines: Integrate with Continuous Integration/Continuous Deployment tools like Jenkins, AWS CodePipeline, or GitHub Actions to enable automated testing with each build. Test Management Tools: Connect with tools like JIRA, TestRail, or Zephyr for tracking test cases and reporting results. Reporting and Logging: Implement detailed reporting (e.g., Allure, Extent Reports) and logging mechanisms for clear test results and debugging.

Framework for a Project vs Enterprise Framework: When designing a framework, it is crucial to take into account the distinction between a project framework and an enterprise framework. An latter encompasses a broader scope and involves various departments, systems, and processes within an organization. It necessitates extensive technological support and integrations to cater to the diverse needs of different business units. In contrast, a framework for a program or a project typically has a narrower focus, concentrating on specific objectives and deliverables. While both frameworks require careful planning and consideration, an enterprise framework demands a more comprehensive approach due to its larger scale and complexity.

One of my weaknesses is the endless pursuit of perfection :) I suggest to write clear requirements even if you work alone on your framework, before starting to write/optimize it. Since endless optimization, in pursuit of perfection, may never end. Make the necessary functionality work, deploy it, and only then start to optimize it

Code Review: Regularly review your code to ensure it adheres to best practices. Refactoring: Continuously refactor to improve code

Continuous optimization and refactoring of the code are essential practices to maintain an efficient and effective automation framework. As the project evolves, it's common for the automation code to grow and become more complex. Regular refactoring helps eliminate duplication, simplify logic, and improve readability, making the code easier to maintain. Additionally, optimization can include improving test execution time, reducing dependencies, and adopting new technologies or methodologies that increase efficiency. Proactive code maintenance ensures that automation remains relevant and useful over time.

:= Regularly review and refactor your automation framework code to enhance its performance and maintainability. := Identify and eliminate redundant code, simplify complex methods or classes, and replace hard-coded values with variables or constants. := Extract common code into reusable methods or classes, refactor conditional statements and loops for better encapsulation, and adhere to coding standards and formatting guidelines for consistency and clarity

Existing solutions will never fully meet your requirements, and most probably you will never create your own silver-bullet solution, so, try, fail and try again. There is only one measure of the success in this field and it's an extensive experience

Another useful method is to use existing frameworks instead of building a new framework and check and optimize it according to our needs.

Do analysis which tool/model of the framework will be best suitable and save cost. Implement all the reusable methods in common method. Use inheritance to use the required methods . Implement latest versions of selenium, TestNG so that code will be optimized. Implement proper extent report mechanism. Integrate with Jenkins for faster test results

I've learned that effective communication and collaboration across teams are as crucial as technical adjustments for successful automation projects. Tools and frameworks evolve, but a team's ability to adapt and integrate these changes smoothly often hinges on clear, open communication channels and shared goals.

Building an automation framework is like crafting a powerful engine for testing. You start by carefully planning which tests are most important, such as checking if users can sign up and login. Then, you choose top-notch tools like Cypress or Selenium, which are like the engine's components, to execute your tests smoothly. Next, you write precise code to mimic user actions, like filling out forms and clicking buttons. Additionally, you handle test data with care, ensuring accurate and reliable results. Finally, you continuously fine-tune and enhance your framework based on test outcomes and changing requirements, creating a robust and high-performing testing engine for your application.