Test automation as a key to unlocking business potential
A smart combination of manual and automated testing can optimize QA efforts and help meet tight deadlines. How to introduce test automation? What challenges may arise? Find the answer in the article.
Within the era of wide-spread digital transformation and a shift to enterprise agility, companies strive to optimize processes and develop smart workflows — all to improve business effectiveness, stick to set budgets, maximally neutralize any risks, and be prepared for any sudden twists and turns. For instance, enterprises may give preference to RPA, introduce electronic records management systems, rely on AI/ML technologies, and more.
The software testing industry is no exception and has also has the need to simplify work and accelerate delivery velocity. Test automation has become an ideal candidate to achieve these outcomes due to the multiple benefits it provides for business. However, its introduction isn’t a walk in the park.
Therefore, in the article I’ll highlight its essence, challenges, and best practices for successful implementation.
Test automation at a glance: is it worth introducing?
Automated testing has continued to be a buzzword for many years now. Companies of diverse scale and across different industries supplement their manual testing efforts with automation. But why? The World Quality Report 2023–24 (WQR) states that they see neutralization of risks (54%), more effective testing workflows (52%), and lowered number of issues in the production environment (51%) as the benefits of its implementation.
In addition, organizations that give preference to automated scripts can also see other benefits, including but not limited to:
- Boosted velocity. Accelerated test execution speed is one of the biggest test automation perks. For instance, with a tailored QA automation approach, a well-known Japanese corporation managed a 22.5 x speed increase in regression testing.
- Continuous test runs. With the ability to schedule tests, QA automation engineers can set up the necessary time of executing tests, even at night, and afterward analyze provided statistics.
- Effective scalability. With manual testing, it’s more difficult to cope with increased number of test cases, while test automation allows performing them without significantly expanding the QA team.
- Reusability of tests. Each written script can be slightly adjusted to also check software on diverse platforms, devices, or OSs, which has a great time and financial saving benefit.
To maximize its positive effects, companies can also make use of advanced automation practices. First, I’d mention low/no code automated testing. Its essence is clear from the title — they decrease usage of code and, thus, can be leveraged by a wide variety of specialists. Such solutions require less time to generate automated scripts due to in-built templates and ensure easier test maintenance because of an ability to rapidly adjust to any software alterations.
The usage of AI/ML is another game-changing practice leveraged in test automation that has already proved its effectiveness. By embedding this technology into the test automation landscape, project teams can optimize workflows in many ways such as:
- Accelerated time of test results analysis that involves processing of large data amounts.
- Predictability of software issues due to AI’s capability to learn from already executed scripts.
Major roadblocks complicating test automation introduction
Before delving into the test automation implementation journey, I’d recommend that companies learn about its most challenging aspects to better understand what they might face and how to address these hurdles in the best way. I think the top 3 considerations are:
- Acute deficiency in proficient specialists
To be able to set up automated workflows from scratch, specialists should master sought-after programming languages, know how to correctly define scope and tools, how to improve or develop customized frameworks, prepare test data, analyze results, establish monitoring, and integrate an automated solution into CI/CD pipelines. In addition, skills related to testing AI-driven software or using AI during testing also come to the fore.
Thus, organizations should establish an all-embracing plan for practical-oriented training sessions either performed by senior specialists or third-party experts. The training should include workshops, seminars, master classes, webinars and cover areas where knowledge gaps are observed.
- Picking fit-for-purpose tools
The modern market can offer a myriad of free or chargeable solutions for running automated verifications that work well with different programming languages. They can be used immediately after installation or may require some adjustments. When facing such a wide selection of options, companies may be overwhelmed.
To make the right choice, I suggest conducting in-depth research to analyze the tool’s capabilities and make sure it’s compatible with other already leveraged solutions. The choice should also depend on vital characteristics such as price, user-friendliness, and scalability to support increased testing needs in the future without changing the toolkit.
- Keeping everything in order
As the project evolves, the software’s functionality grows, which means that more automated tests need to be adjusted to support error-free application work. Over time, this task may become daunting.
Therefore, project teams can leverage VCS solutions to easily monitor any alterations in the code of automated tests, trace who made them, and return to previous variants if necessary. It’s also a good idea to set up a schedule for updating existing tests so that they match the IT product’s features.
Best practices to seamlessly infuse automated workflows
When a company has decided to strengthen its manual testing efforts with automation, I’d bear in mind some practices that can be useful and can simplify the process.
- Define and prioritize required efforts
Choosing what verifications should be automated and in what order is of crucial importance. Project teams should prioritize their testing efforts, meaning that verifications that cover the most critical business functionality used most often by end users, deal with extensive data amounts, or sensitive software features prone to issues that can cause severe financial consequences should be automated first.
2. Configure the execution environment
This step is of high importance as it directly influences the success of the QA activities. Apart from provisioning all necessary software, hardware, and test data, it’s vital to make sure that the testing environment is properly configured and allows testing different features in isolation. I’d also recommend that someone takes accountability for its correct operation and availability round the clock. In addition, all aspects related to your environment should be tracked in a detailed documentation to simplify and speed up onboarding of new team members.
3. Select appropriate toolkit
To select fit-for-purpose tools, it’s crucial to consider a variety of project aspects. The toolkit should support the applied programming language and platform — for instance, if you need to run tests on both Android and iOS, you may either need 2 separate tools or develop a tailored framework for writing a single test suitable for both platforms.
The software utilized for testing should be user-friendly and intuitive, but at the same time it must contain all cutting-edge, sophisticated functionalities for performing necessary tasks, allow for comprehensive reporting, and work well with existing CI/CD solutions. If financial opportunities don’t allow acquiring pricey tools, there’s always a possibility to opt for no-cost solutions. In addition, if the team is proficient, they can build a customized test automation framework for their individual project needs themselves.
4. Design and run automated scripts
After preparing everything and gaining a clear understanding of what to automate according to set business needs (as automation of the entire software product is rarely possible), it’s time to write scripts. When preparing real-world verifications, it’s important to avoid test flakiness, when tests deliver different results without any change in conditions. To prevent such cases, QA automation teams need to continuously observe testing outcomes and leverage quality data.
As for test execution, I’d advise QA teams to execute multiple tests simultaneously with the help of cloud infrastructure to increase testing velocity, lower expenses, and broaden coverage.
Reporting also plays a pivotal role as it helps specialists to obtain a bird’s-eye view of the testing process and make better decisions based on obtained data. Advanced visualization that includes charts, graphics, tables, or drawings simplifies data representation for stakeholders.
5. Take care of existing tests
Over time, the application will inevitably grow, changes may be introduced to it, or both, which means that tests can become outdated. Therefore, it’s vital to give due attention to their updating. Additionally, to ease maintenance, I’d suggest writing small tests that verify only one aspect.
6. Monitor progress with special KPIs
To make sure test automation brings expected results, QA managers can continuously measure success with suitable metrics. I think the handiest ones are those that indicate the number of passed or failed tests, the number of detected issues and problems in the production environment, total test coverage, and time saved compared to manual execution. With these KPI’s QA teams can have a big picture of the entire automation processes, optimize their effectiveness, ensure smarter utilization of available resources, and gauge reliability of the existing test automation solution.
Summing up
Test automation is a game-changer for long-term projects that deal with a large number of repetitive tests that take long time to execute. It ensures faster software delivery, extended test coverage, reduction of human error risks, and earlier identification of issues.
To put this practice into action, companies can define and prioritize efforts, set up the execution environment, choose the toolkit, design and run automated scripts, maintain tests, and leverage KPIs to track progress. And be confident in ongoing efforts and further success!
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