Software Test Automation Strategy: Tutorial and Guide

A software test automation strategy is a comprehensive plan that outlines the approach, tools, and processes for automating software testing activities within an organization. It defines the scope, objectives, and guidelines for implementing automated testing solutions. Ultimately, it aims to improve the software testing process's efficiency, reliability, and speed.

However, implementing a successful test automation strategy is not a one-size-fits-all approach. It requires careful planning, the right tools, and a collaborative effort from the entire development team. This article explores the critical elements of a practical test automation strategy—from setting clear goals and selecting the right tools to managing test data and fostering a high-quality culture—with a focus on specific best practices for success.

By the end of this article, you will have a comprehensive understanding of how to create a robust and efficient test automation strategy that not only catches bugs but also accelerates your development process and enhances the overall quality of your software. So, let's dive in and unlock the full potential of test automation to take your software testing to the next level.

Summary of key software test automation strategy best practices

Below is an overview of the concepts and practices we explore in this article.

Define clear automation goals

“What are we testing?” This is a simple question with many answers. Misalignment can come from many places: outdated documentation, miscommunication among teams, or an automation plan never being specified before beginning work. Teams must be aligned on where, how, and what they are testing, but it is surprising how easily these concepts can become misaligned as people and projects change.

Defining a goal can and should be done as a team. Collectively, you all need to decide what tools will be used, what environments and devices you will be testing, and the boundaries of your testing. You will want to do this exercise at each testing level: unit, integration, system, and acceptance.

To understand the scope of testing, it is essential to look at auxiliary test types beyond the testing of features. Is performance testing needed for scaling? Are we doing security or compliance testing? Are we risk-averse?

By setting goals, the team can stay aligned and deliver the highest impact against the business's quality measures.

Choose the right automation tools

Choosing tools ahead of time is crucial to any test automation implementation, and getting the right tools is even more important. But what does it mean to have the right tools? Here are the most significant aspects to consider:

• Usability: The tooling selected should match the engineering team's pre-existing skill sets. This makes test implementation easier and quicker. Also, usability prevents “context switching,” where developers switch from a development context into another less productive context. Tools requiring extensive training or steep learning curves may reduce productivity in the short term, even if they offer long-term benefits, so selecting a tool with the right balance is essential.
• Maintainability: Tests need to be easy to maintain; as a codebase changes and scales over time, so must the tests. Making tests maintainable means that updating older tests becomes easier for developers. It also reduces the time it takes to update tests and create them for new features or code changes.
• Scalability: Test scaling is an often overlooked aspect of the planning process, but as you increase the number of tests, you need to consider how your framework will look in the long run. Tests must be manageable as complexity rises, and strategies are needed to keep the test suite stable and execution time minimal.
• Modularity: By having a test suite that is modular, it is possible to support tests at scale and produce a more maintainable framework. Modularity means taking advantage of classes, templates, fixtures, and other centralization strategies for your tests.

The biggest takeaway is that test automation is a team effort, and the tools must work best for the team and the project.

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Seamlessly execute tests

Part of a good software testing automation strategy is understanding where the tests will be executed and how. There are two aspects to look at when discussing test execution.

The first thing to consider is how the tests run locally. Local development—and, by extension, local testing—should be a seamless process where developers can execute tests rapidly and as often as needed. This design prevents long delays when code changes are pushed that fail quality gates in upstream executions.

The other aspect of test execution is running the tests in the continuous delivery and integration pipeline. Tests should be run as often as possible between environmental, configuration, and code changes. With execution tools like CircleCI, Github Actions, and Gitlab CI/CD, you can easily run the tests as part of your deployment pipelines.

Some providers, such as Qualiti, go even further and provide an entirely seamless experience for executing tests automatically. Qualiti allows you to configure your test environment in moments. Add a new testing environment for each stage of testing, such as Dev and Staging. In your test library, you can see your test suites as well as AI-powered suggestions for test case groupings.

Implement robust data management

You cannot even begin to test without understanding the data you will use for testing. A great basic example that nearly every application has is the user. What attributes does the user have in your product? What will the user do and do they have any differentiating factors? In fact, the question is not just “who is this user?” but also “where will we store the user’s information?”

When managing data, don’t simply ask who or what can access it. It’s important to determine where to store data and how best to retrieve it. Tests should store data centrally so that only one copy of each set exists; that is, all test data should only have one source of truth. This is crucial because test code regression bugs can occur when test data does not match new requirements or features.

Test data also needs to reflect the production environment as much as possible. Realistic test sets lead to realistic bugs that your users may experience. Having incomplete or inaccurate data sets can lead to false positives when testing and even allow bugs to escape into production.

Finally, keep in mind the need to keep test data clean. The data produced should be isolated to just the tests so you do not accidentally impact users, and it should be cleaned up so that the user experience cannot be affected in other environments. Testing at scale does not excuse the generation of faulty production data!

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Implement continuous monitoring

Another component of a great strategy is how you monitor and record your automated tests as they run. Tests lose value if engineers cannot see what is wrong as quickly as possible, and they also need to be able to show application health trends so that informed decisions can be made on how to improve the product.

Agreement is needed on what data to use, how to generate it, and what possible error scenarios are and how best to prevent them. This can involve coordination among engineers, stakeholders, customers, and others. Continuous monitoring and reporting aid engineering teams in communicating real-time system information to non-technical personnel.

Run great tests in a great environment

A common issue that occurs all too often is when automated tests pass in Chrome on a pre-production environment, but a bug on Safari occurs in production under the same testing steps. What went wrong is obvious: Either there is a browser-specific issue or a configuration parity issue with production and preproduction. However, for dynamic teams, how to methodically troubleshoot and mitigate newly emerging issues as they arise can be a big question.

Test strategies need to account for where your customers use your product. Browsers, platforms, and devices should be considered and measured to get a good idea of where the tests should run; for example, if most customers use Chrome on Windows, then tests should primarily run there. Several publicly available packages and tools can help collect this information.

Tools like Qualiti can provide methods to easily test differing environments:

The second aspect of your strategy is to examine all application environments. How many tests should be run in each environment, and how feasible are they to run there? Are there any differences in the environments to account for?

Qualiti again supports this concept with environment and credential management:

Consistency in testing environments leads to fewer defects and facilitates informed feature and test prioritization decision-making.

Foster a culture of quality

As the article has touched on several times, quality is not just an individual responsibility—it is a team responsibility. The “team” refers to both technical and non-technical contributors, all of whom can and should all advocate for quality in the product. When everyone understands and accepts the impact of a high-quality product, they can be better aligned to implement features that delight customers.

What you can do to foster quality is quite simple: Think like the customer. That’s it. Quality will come naturally when you think about the product with a customer focus and advocate for the customer in all parts of your development lifecycle.

Everyone can (and should) contribute to the test automation strategy.

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Last thoughts

Embracing test automation is not just about catching bugs faster; it's about enabling development teams to deliver high-quality software more frequently and confidently.

By incorporating automated tests into continuous integration and delivery pipelines, organizations can receive faster feedback, detect defects earlier, and ultimately provide a better user experience for their customers.

However, it's essential to recognize that test automation is not a silver bullet. It requires ongoing effort, collaboration, and adaptation as applications and technologies evolve. Regular review and updates to the test automation strategy ensure that it remains aligned with the organization's goals and keeps pace with the ever-changing software development ecosystem.