Test Automation Guide: Unlocking Fast Routes to Greater Results

Sam Syzov
Alina Ampilogova

The emergence of new approaches, rising complexities, and the demand for increased speed to market change the way companies deliver and test products. While production failures are no longer deemed acceptable or expense-worthy, forward-thinking leaders focus on reinforcing their testing teams with technological leverage. 

Following that demand, test automation became a game changer for many companies, enabling rapid validation, faster release cycles, and enhanced product quality. Yet, as with any automation, it involves critical aspects that decision-makers should consider and carefully plan at the outset.

To provide executives with a 360° perspective, we created this complete guide to test automation, its benefits, the difference it can make, and the steps toward building a functional and successful test automation strategy. 

Types of automated software testing

Before going deep into the details, there is a point in starting this test automation guide by recalling the main software testing types.

Performance testing

Evaluating the system’s ability to operate under an expected workload, its capacity limits, breakpoints, and behavior under sustained use and sudden load spikes. 

Functional testing

Testing different system functions within expected requirements by creating input and output data based on the function’s specifications and comparing them with actual outputs received after test execution.

Regression testing

Verifying software performance after a change or an update by re-running all the tests executed for the previous version and checking the results. 

API testing

Assessing API functionality and its communication with different systems by sending requests to endpoints (multiple and single) and validating key user journeys.

Integration testing

Checking the compliance of a system or a complement with specific functional requirements or testing the ability of different software modules to work together.

ETL testing

Securing the correct extraction of data from its source, its proper transfer and loading to the new system within such activities as setting new data warehouses, adding new data sources as well as data integration or migration.

Given that every repetitive process can be automated and each of the software test types mentioned above has its repetitive steps, it makes automation testing possible, unlocking new value for testers, development teams, and businesses.

Why do businesses need test automation?

To fully outline the importance of test automation in steady product development and product quality management, it’s important to dissect the factors that affect manual testing and can make an impact on the final result.

Managing growing pains

Every long-term digital product will inevitably grow and change, getting more integrations, and expanding to new platforms. Ultimately, it starts requiring more testing and increased test coverage to ensure smooth feature performance. Additionally, QA teams need to run more regression testing to ensure that all the implemented changes don’t cause disruptions or break the software. 

However, with the product increasingly growing in size and complexity, regression testing cycles, too, grow longer—and since regression testing is a very repetitive process, regression failures may become quite common due to tester teams overlooking hidden issues due to having to perform the same process over and over again.

Hiring or training more QA experts might look like a solution to these problems, but it takes time and budget (while improvements are quite often needed right here and right now). Not to mention, the growing demand to meet the newly emerging needs. So, test automation provides an alternative: equipping testers with automation testing tools that can perform regression testing of massive structures within a fixed amount of time, while providing experts with visible testing metrics and notifying them of issues.

Inconsistent test results

The more tests teams have to run, the more people get involved in the process, the higher the risk of losing track of relevant test metrics. As a result, performed tests may bring different or inaccurate results each time, sabotaging the quality of the final product or a feature update. 

Therefore, creating a stable framework locked on the key metrics and keeping them in front of tester teams and dev teams is crucial to releasing products or necessary feature updates on time and without potential complications.

Navigating fast-paced environments

Some development cycles are very intense and dynamic—for instance, mobile app development is particularly intolerant of delays and setbacks. Due to this, testers often find themselves under increased pressure, having limited time to perform crucial testing and feature quality assurance, which increases the risk of missed bugs or vulnerabilities. 

Not addressing the latter in time can potentially lead to more than ruined user experience: in case vulnerabilities affect user data or other sensitive information, the damage will cause millions of dollars to compensate. Meanwhile, the reputational damage will remain. 

When testers have limited time for testing, but want to run the app through as many tests as possible, test automation backs them up, saving time by reducing manual steps and lets them focus on issues identified rather than on routines.

Lacking close-to-real test environments

To deliver the most accurate results, testers need to make sure their testing environment represents the product in its entirety, complete with configuration and the variety of potential scenarios. 

This is particularly important for compatibility testing, when testing teams need to be certain that software works smoothly across all the platforms/combinations. Doing so manually, however, once again opens a door to multiple possibilities of human error in addition to being generally time-consuming.

Key test automation benefits: faster delivery, reduced risks, and greater rewards

Considering the testing challenges mentioned above, test automation equips testers and developers with all the utilities and tools they need to operate efficiently even in the most dynamic environments.

When exploring the value of a test automation approach, there are several crucial benefits to keep in mind:

  • Faster time-to-market time
    According to Forbes, debugging should take only 20% of the developers’ time, while the rest should be dedicated to value-focused activities. When debugging takes more time, it’s a clear sign of underlying development issues that can result in a failure to meet established deadlines. An incorrect approach to testing is often the most common reason for sudden delays. 

    For instance, sometimes the product is moved to testing after development—where testers detect critical issues that need time to fix and even more testing afterward, resulting in a moved release date and additional expenses. Test automation makes it possible to run tests in parallel with the development processes, allowing to considerably accelerate product delivery cycles and make it to the scheduled deadline. 

  • Facilitated risk management
    A software bug can cost a company millions of dollars. A vulnerability brought by the Tesla Full Self-Driving Software update caused Tesla stock to fall 5.7% to 201.97%. A defective IT system resulted in Horizon wrongly convicting 736 of its employees of theft and then being obliged to pay over 1 billion GBP in compensation. These cases show the impact an overlooked issue can have on a business, no matter its size or history. 

    Test automation allows to minimize such risks due to a greater test coverage that encompasses a broader range of scenarios and enables early identification of critical issues affecting performance or even user safety. Accordingly, companies manage to create a stable and more controlled testing environment while being more confident about their software reliability.

  • Greater cost control
    While around 52.4% of Word Quality Report respondents’ teams acknowledge achieving improved cost control by leveraging automation testing, it’s worth noting that test automation shouldn’t be perceived through the money-saving lens. Project development will always be an expensive effort and the cost shouldn’t be cut at the QA expense and testing phases. Test automation makes it possible to save resources in a way that counts—by enabling early error fixing (which can cost up to a hundred dollars instead of thousands of dollars if detected at the pre-release stage) and preventing financial loss due to dangerous errors making it to the released product.

    In other words, a test automation approach gives companies more control over their funds by averting unforeseen challenges or issues that can make leaders and executives go beyond their planned budget limits. Such an improvement translates into better and more efficient budget planning that enables companies to make value out of every cent they invest.

  • Easy consistent quality maintenance
    Releasing a competitive digital product on time is half the battle. The long-term success depends on the company’s ability to maintain the product’s uninterrupted functionality, deliver timely updates and avoid sudden breaks, introduce new integrations, and maintain a high user experience.

    Since a great start leads to great growth, test automation will become a constant part of product quality maintenance, providing facilitated issue monitoring, accelerated regression testing, and interaction testing. Using automation in testing at every stage of development and as a quality management measure makes it possible to provide end users with exactly what they expect—continuous improvement balanced with complete stability.
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New technology in test automation: focus on intelligence, digital twins, and early-stage prevention

Projected to grow to 51.26 billion USD by 2030, the test automation solutions market demonstrates a promising growth trajectory, which is fueled by the rapid evolution of test automation technologies. For executives and decision-makers navigating the abundance of tools, trends and applications, there are several developments to consider:

  • AI test automation
    The future of automation is intelligent; Having made great strides across enterprise data analysis, document validation and organization, marketing content generation, and coding, artificial intelligence is seen as a Holy Grail of test automation. While implementing AI is certainly possible and provides a number of valuable advantages, it should be done with a clear and realistic understanding of what this technology can bring to the table. 

    For instance, AI enhances test automation with extra precision and intelligent algorithms that streamline previously difficult and time-consuming tasks.

Investigating unidentified objects that break script by extracting script objects and putting them through similarity-scoring algorithms until the objects are identified. 

Codeless testing

Faster processing of requests and business scenarios, facilitated test maintenance and user behavior imitation.

Improved visual regression testing

Checking how web app interfaces and software dashboards match the designed mockup and revealing even the slightest inaccuracies.

Albeit such improvements make a lot of difference in testing, AI has constraints of its own: it lacks flexibility for dealing with too many new variables and new tasks, it’s very reliant on the quality of data it’s provided with, and it can’t cover major issues (logic flaws, usability). Therefore, choosing AI-powered automation testing should be a decision based on specific goals and issue types, not over-exaggerated expectations.

AI in test automation: finding a balance between hype and reality
  • Focus on early defect prevention
    As soon as the correlation between fixing issues as early as possible and saved development costs was established, companies made a decisive shift towards empowering testing teams with more tools and options for detecting bugs and vulnerabilities during the first stages of a software development cycle. It’s expected that test automation tools will be enhanced with a number of technologies, such as:
Data analytics

Tracking and recording real software user behaviors for better understanding of their interactions with the product, therefore improving testing and development quality.

Intelligent automation

Providing fast data extraction and entry to supply teams with reports across the entire testing cycle.

Predictive analytics

Enriching automation tools with data-driven capacity, enabling accurate predictive analytics.

It’s noteworthy that the shift of attention towards the earlier stages of development isn’t just a trend. This change is here to stay. 

The more visibility and data teams have on their hands—and the more data can be incorporated into test automation tools, the faster the development routines will get.

  • Digital twins
    Expected to hit 183 billion USD in 2031, the digital twin solutions market is growing rapidly due to its potential to bridge the gap between virtual and physical reality. In the context of such growth, the appearance of digital twin models with built-in test automation tools was a matter of time as it enabled faster and efficient digital twin creation. 
Enhanced validation and verification

Ensuring the digital twin models match the expected specifications by evaluating their logic and functionality, detecting errors, and bugs.

More accurate sensitivity and uncertainty analysis

Analyzing the twin’s ability to respond to sudden changes (new inputs, assumptions, and parameters), estimating the levels of potential error and limitations of the model.

Behavior-driven development document processing

Assessing how the digital model responds to expected user behaviors and interactions and whether these responses match the flows outlined in development.

Creating accurate digital twin models is an essential component of successful operations across manufacturing, supply chains, and even agriculture—which makes test automation solutions a vital addition to the technology.

Test automation strategy: what does an automated testing lifecycle look like?

Speaking of how test automation usually occurs, the process itself is easy to break down into stages:

1) Scope definition

The test automation team examines the project in question and assesses the scope of work. At this first step, having a detailed knowledge of testing environments is crucial as it allows detecting the main pain points and the most time-consuming parts of testing. Within scope definition, need discovery currently occurs as decision-makers may learn of the issues and constraints that used to fly under their radar.

2) Establishing communication

Choosing the right implementation course and test automation approach is directly correlated with the quality of communication between the test automation teams and testing teams. Their insights and feedback become the baseline for the future test automation pipeline and strategy as well as the communication and cross-collaboration enablement options.

3) Validating the scope of test automation

After discovering the needs and communicating with testers, the test automation team applies their updated perspective to the scope and gets a clearer picture of the testing environments and how they can be improved. This is where test strategies are planned out and designed.

4) Automating test environments

Following the outlined strategy, the test automation team applies changes to the testing flows and sets up new, automated test environments with expanded coverage and a clear view of key testing metrics.

5) Enabling reporting

Testing teams and QA teams are provided with a robust feedback loop for getting updated on testing outcomes in a way that is convenient to them: through existing enterprise systems or by email. Within a test automation cycle, reporting plays a major role, keeping development teams and testing teams updated on testing progress and testing outcomes.

6) Securing smooth execution

To make sure that testers can run necessary tests at any time, the test automation team builds intuitive and easy-to-launch CI/CD pipelines and delivers all the important documentation to testing teams.

This is how a test automation cycle looks from the test automation experts’ perspective. As a rule when we assist our partners with automating their testing routines, communication and collaboration become the cornerstone of our strategy, regardless of the framework. We provide our professional angle on their existing environments and make suggestions that address the core of their testing issues. Meanwhile, testing teams outline the desired testing pipeline, which allows creation of solutions that hit all the boxes.

Checklist to implement test automation: how to make all components click together?

With test automation types, benefits, and technologies outlined, it’s time to go through the key steps to setting up a functional and results-rich test automation framework.

1) Identifying test automation goals

Before jumping on the automation bandwagon, companies need to first understand and identify their primary need for test automation. Whether it’s about improved accuracy, reduced QA team load, faster execution across CI/CD pipelines, or increased test coverage—each goal should be tied to a specific context.

In some cases, automated testing should target specific use cases to provide fast, easily digestible results. For instance, for applications with sensitive content and pixel-perfect design, businesses run automated UI tests to reveal inconsistencies (previously undiscovered during manual testing).

Whereas for scenarios involving critical infrastructure and multiple dependencies, test automation is often launched with maximum coverage (e.g., during the night). This way, it reduces the manual load for regression testing and helps businesses avoid costly failures or unscheduled downtime.

Having a clear vision of the goals you’d like to pursue is foundational to ensuring your test automation strategy targets the right issues and brings desirable outcomes.

2) Breaking misconceptions to reinforce testing teams

Many company leaders think of automated testing as a universal solution to all their software testing challenges or even a replacement for traditional quality assurance. However, manual QA and test automation target different goals and therefore should work in sync—complementing and reinforcing one another.

Automated testing liberates the manual QA team’s time by mimicking repetitive tasks and shifting their focus to higher-value activities. It follows specific algorithms and allows for higher availability, reusability, and accuracy. For instance, running tests around the clock and simultaneously helps with increasing coverage and reducing tester fatigue. It also empowers the QA and development teams to reveal defects earlier.

The most comprehensive understanding of an application’s health comes from utilizing both techniques and thus enabling increased cost-efficiency, manual error reduction, faster turnaround times, and enhanced testing coverage at a better scale

3) Choosing the right technology foundation

Implementing test automation is a long-term strategic choice and should be approached as such. Setting the right technology foundation can help decision-makers minimize reworks and future-proof their software solutions apps in the long run.

When evaluating automation tools, executives also need to identify critical areas and technologies that could be potential targets for automation as well as review their team’s capabilities and market availability of experts with matching skill sets.

Choosing rare or emerging tools that don’t match your current environment and team‘s knowledge can perplex new technology adoption. While staffing, onboarding, and training the right people can turn out a challenge, making your automation budgets less controllable. Or even put your application's success at risk, as emerging frameworks might not hit the expected KPIs.

The result? Your delivery timelines and expenses grow exponentially as new flags arise.

Companies can relieve this pain by selecting a reputable automation library (e.g., Playwright from Microsoft or Facebook’s Jest) that:

  • Has matching capabilities and supports enterprise platforms and tech
  • Is flexible and easy to use for all the parties involved
  • Creates tests that are maintainable and resistant to UI changes
  • Integrates well with the enterprise CI/CD pipeline and current ecosystem

4) Connecting silos to maximize impact

Running autotests locally, without setting them up in development environments, leads to a lack of synchronization between the teams and longer turnaround times.

To break down silos, companies need to ensure a proper connection between development and testing. It can be done in a form of providing access to the test environments for the right people to run tests and check the solution's quality when needed. There is also an alternative of integrating autotests in the CI/CD pipeline to send alerts and automated reports to the development team, making test results more visible.

Creating a shared understanding between these teams will help you reduce failure demand and overhead expenses.

Depending on the project’s context, you need to identify people responsible for the results and creation of action items (based on test results). A clear definition of responsibilities and complete process transparency will accelerate the time-to-resolution for defects and streamline release cycles.

5) Targeting the right automation candidates

Automated tests are fast, effective, and reliable when they are targeting specific areas instead of huge test flows. Therefore, automating manual test cases (instead of functionality) is a quality engineering anti-pattern that inevitably leads to bloated and hard-to-maintain test suites — providing little to no value.

To ensure autotests are designed properly and bring value, businesses need to shape the acceptance criteria and identify areas that require additional coverage. Usually, these areas include:

  • Critical functionality (with multiple dependencies)
  • Most in-use functionality
  • Aspects that are draining for your manual QA team
Your quality assurance team should prioritize critical features for automation and present functional requirements so that automation experts could better design and develop their autotests. Such a holistic approach to automation and workflow scenario design is critical to maximizing test coverage and maintainability.

How to keep up with test automation challenges and best practices?

While test automation is meant to simplify and accelerate testing routines, it takes more than a test automation guide to overcome several challenges before building the perfect test automation strategy. 

Aside from testing teams’ misconceptions about the purpose of test automation, executives and decision-makers may hesitate to implement test automation for such reasons as:

  • Lack of expertise
    Sometimes, testing teams don’t have experience with test automation tools and solutions, which impacts their experience. For that reason, onboarding testing teams and communicating with them to gradually introduce them to innovation and ensure productive friction-free interactions.

  • Having wrong test automation expectations
    Like intelligent automation, test automation is not a one-time project, nor is it a silver bullet or a replacement for manual teams. It’s also worth remembering that not all tests can be automated —- a fraction of them will always need to be handled by human experts. Accordingly, decision-makers need to leverage test automation as an enabler of their human teams while adopting a fresher mindset towards their development cycles. Only by being flexible and proactive, can they enable consistent testing that accompanies every development stage, keeps key metrics in front of all the teams and secures desired outcomes.  

  • Lack of test infrastructure
    A greater test coverage needs a proper, robust infrastructure. Mostly, the one that can support testing software against various OS/browser combos and other configurations. Additionally, to save time, such tests are performed in parallel to each other—which creates a rather intense load. To build an infrastructure capable of operating such conditions while optimizing expenses, it’s possible to use cloud-based infrastructure that enables all testing operations without straining enterprise resources.

  • Previous bad experiences
    Getting bad or underwhelming results from a previous test automation attempt can dissuade decision-makers from continuing. However, abandoning test automation is not an option in highly competitive environments that depend on keeping up with growing user demands and maintaining operational efficiency. Projects don’t stop growing and challenges continue to pile up, so the sooner testing teams are empowered with powerful test automation suites, the more value can be injected into development cycles. For that reason, decision-makers are recommended to take an investigative approach to their negative experience, identifying what went wrong and then using that knowledge to design a strategy that works for them.

While test automation can be challenging, every problem comes with a solution. The key to succeeding at automation testing lies in careful planning and thoughtful risk mitigation. Before decision-makers get started with their test automation efforts, they should map out a full implementation journey, complete with roadblocks, needs that should be covered, and skills they require. Afterward, they need to evaluate their team's current experience and familiarity with test automation solutions as well as the time and funds they’re willing to invest. 

Such a scrupulous test automation approach becomes much easier to realize when decision-makers join efforts with trained and committed test automation partners.If you’re currently interested in amplifying your productivity potential with sophisticated test automation solutions let’s chat! Having successfully enabled value-driving test automation pipelines for our Fortune 500 clients, our test automation experts will help you map out and execute the right strategy to unlock long-term value and boost delivery velocity.


Test automation is the methodology of automating tests performed by testing teams to check software quality and feature functionality. The purpose of test automation is to optimize testing performance, increasing the quality and consistency of outcomes while reducing the time spent on testing. While generally considered a practice for QA teams, test automation plays a significant role for developers and business analysts because it allows more opportunities for innovative feature development, and provides a detailed dissection of product value and its ability to follow the business logic.
Tests eligible for automation have several criteria. First, they're repeatable, following the pattern of setting up the data and the environment, executing the test, and returning the environment and the data to the base state after the test is over. Second, the tested function should be a determinant i.e. delivering the same outcome after being run with the same input. Third, it shouldn’t be opinionated, which is why tests like beta testing or usability testing can’t be automated and are always handled by human teams.
Test automation frameworks are an integral part of the process as they contain repository management, test data processing, and coding standards instructions that developers and testers should follow. Basically, automation frameworks are sets of guidelines that optimize testing routines and costs, while providing value to the teams. There are various types of frameworks that can be used within a test automation cycle. Linear frameworks are the very definition of automated testing. Simple and sequential, they are characterized by the scripts that are written and executed without the tester’s participation, which makes them a great choice for non-coded function creation. In addition, linear automation frameworks are often used for small app testing as they are quick, allow fast script generation and don’t require deep automation expertise to launch and monitor. Modular-based frameworks divide the software into several modules and test each other separately within individual test scripts before being tested altogether. Data-driven frameworks allow testing the same software or function with different data sets, several times through testing script logic separately from the test data. Keyword-based frameworks, designed to amplify the usability of scripts and cover more tests without having to invest too many resources in maintenance work similar to data-driven frameworks. However, they use high-level and low-level keywords that represent different test case behaviors, with each activity being labeled with a specific keyword.  Meanwhile, there are also hybrid frameworks, which, as the name implies, combine elements from the rest of frameworks to meet specific testing goals and needs.
Using test automation in business environments provides businesses with a number of advantages, with risk control being the most important. A flaw in a digital product or an IT system and lead to huge financial losses and tons of reputational damage. To avoid this, businesses need to pay attention to the way the product is developed and tested for bugs and vulnerabilities.  Test automation enables this by allowing to locate issues at early stages when they’re more cost-effective to fix. Greater visibility makes enterprises more confident about their in-house systems as well as the products they offer to their partners and customers, which empowers them to advance their planning and continue their growth journey.
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