Jaspar Casey - 5 January 2021
Automation drives significant business improvements by helping organizations get more from their people, processes, and technology. While this has implications for virtually every sector, perhaps one of the most significant is in the area of software and application testing. As Gartner senior director Joachim Herschmann puts it:
“There is a challenge to testing in the sense that we need to do it more frequently, we need to do it for more complex applications, and we need to do it at a higher scale. This is not feasible without automation, so test automation is a must.”
Want to know more about test automation and what it can do for your business? Read on for a brief explainer of the technology and answers to some common questions.
What is Automated Testing?
Automated testing automates repetitive, rule-based tasks, enabling teams to both accelerate testing and increase test coverage. According to Gartner, “Automated tests provide consistent results and data points.” Among the many benefits of automated testing are:
- Accelerated testing: test more things faster
- Cost savings: test during off-peak hours and let humans work on more interesting things
- Reliability: increased test coverage leads to better digital products
- Alignment with DevOps and agile practices
It’s important to understand what can be accomplished through automated testing. We’ve all heard the old adage that the customer is king. This monarch takes any number of forms:
- a tech-savvy eCommerce shopper
- a frontline healthcare worker
- an astronaut navigating mission critical technology
- an HR worker accessing an internal application
What do these diverse users have in common? The expectation for seamless, high-quality digital experiences across platforms and devices. This demand is a key driver of automated testing, enabling companies to better meet customers’ expectations while also increasing the speed of improvements to the technology.
Types of Test Automation
There are a variety of testing types that can be automated:
- Unit Testing, which enables teams to test the individual units of source code and ensure they are working as intended.
- Smoke Testing, which tests the software’s most critical features to ensure they are working properly.
- Functional Testing, which ascertain whether all the components of a digital product operate correctly, with a focus on the interface and ensuring user requirements are met.
- Integration Testing, which ensures that all application modules communicate as required.
- Regression Testing, whose purpose is to confirm that any recent code changes have not had a negative impact on the existing features of the website or application.
Benefits of Test Automation
There are numerous benefits of automated testing, including:
- Accelerated Testing
Teams are exponentially more productive when repetitive, rule-based tasks are automated.
- Cost Savings
Test automation shortens the testing cycle, which frees up resources to focus on different types of testing and start on new projects sooner — all of which have a positive impact on the bottom line.
Automated testing enables companies to increase test coverage. It follows that this increased coverage means teams can spot and address more bugs more efficiently, leading to a more reliable and better-performing application overall.
- Aligning to Agile and DevOps
Modern automation removes the perception of testing as a bottleneck, enabling companies to keep pace with the speed of agile and DevOps without sacrificing quality.
Common Myths about Test Automation
It’s not uncommon for advances in technology to have their fair share of ambiguity and confusion. Software test automation is no exception. Here are some common myths about automated testing that are, to put it mildly, not quite right.
- Automated testing requires significant technical expertise. In fact, testing is best when done by domain experts. For example, a UX designer can use test automation software that helps them find and fix bottlenecks in the latest build of their app. Of course, these individuals may need to be supported by technical experts as they iterate on their designs. But as a general rule, the lead testers should be domain experts, and this is reflected in the citizen developer movement. Your choice of test automation software is key to empowering these domain experts who may not be comfortable writing scripts.
- Automated testing is only regression testing. This is a big misconception so let us be clear: nothing could be further from the truth. Model-based testing with AI-powered test optimization can automate tests that have never been executed before. In other words, automated testing can supercharge your testing strategy and allow you to continuously refine the digital experience — all without any additional resources.
- You can’t automate usability testing. By monitoring real user behavior and using AI to understand the drivers of user satisfaction, you can absolutely automate usability testing.
- Test automation requires a complex framework. Creating big test frameworks is quite often a case of too much, too soon. A better approach is to start by writing a few tests, modularize what you create, and get value from those. From there, create some more tests by re-using parts of the original tests where you can. Building up your framework slowly in this way, in parallel to creating real value, is much more likely to result in sustained automation success.
Levels of Test Automation
Thanks to the media buzz surrounding self-driving cars, the average person likely associates automation with the automotive sector more so than with the testing industry. Yet these sectors are not as dissimilar as you might think.
The Society of Automotive Engineers (SAE) has developed a classification system that defines the degree of autonomy by which the vehicle operates. As JD Power explains it, “the driving automation spectrum begins with manually controlled vehicles and ends with completely driverless chariots.”
These levels can also easily be applied to test automation:
- Level 1: Assistance. At this stage of test automation, a human tester writes the test and must maintain it to reflect any changes. The use of AI is limited to performing simple verification steps and assisting with visual checks on the frontend.
- Level 2: Partial Automation. A human tester is still required to write the tests and monitor changes, but at this stage the AI is able to assist with change verification.
- Level 3: Conditional Automation. The balance of work begins to shift at this stage. While the human still must write the test, the AI is now verifying each change and making any updates as needed.
- Level 4: High Automation. The AI has now assumed the test writing responsibility, but the human guides the process and defines what the test should be doing.
- Level 5: Full Automation. At this stage, the AI is entirely responsible for writing and maintaining the tests without any human instruction or assistance.
It will likely be some time before the automotive sector is able to achieve Level 5 at scale. But when it comes to software testing, full automation is entirely possible. Of course, automation can’t solve all modern testing challenges and human involvement is essential for many niche or strategic tests. As such, the trick is determining which tests to automate and optimizing your testing strategy to make use of the right automation level at the right time.
Testing Automation Framework
A test automation framework is a collection of tools and processes working in tandem to support automated testing of the website or application. As mentioned above, it’s a popular misconception that these frameworks must be expansive and complex to fuel widespread automation.
But this isn’t the only mistake companies make when it comes to test automation frameworks. Another common misstep is building their own testing tools based on open-source software. Remember when development teams built their own compilers and systems? This practice is now outdated as numerous standard products exist that can do the same thing — without eating up company time and resources.
The same holds true for the testing industry, and organizations can save a significant amount of time by investing in a testing automation framework. With that in mind, below is an overview of some common test automation framework types:
- Module-Based Testing: In this approach, the “Application Under Test” is divided into numerous logical and isolated modules. Independent test scripts are then created for each module. The modules are separated by an abstraction layer so that changes made in the various sections of the application don’t impact the module.
- Library Architecture Testing: Building on the concept of module-based testing, this framework divides the application into functions rather than creating test scripts. As a result, teams can create a reusable library with common functions for testing.
- Data-Driven Testing: In this approach, the data and test scripts are kept separately, allowing teams to test functionality repeatedly with different data sets.
- Keyword-Driven Testing: This framework builds on the concept behind its data-driven counterpart, organizing data by specific code or keyword.
- Hybrid Testing: This approach is a combination of some of the others outlined above, allowing organizations to build a framework that provides them with the greatest benefits and efficiency.
- Behavior-Driven Testing: This approach enables business analysts and other non-technical groups to actively participate in testing by using a format easily accessible to those without programming expertise.
So, which framework is right for your organization? The answer to that will vary based upon company-specific requirements and, in some cases, individual department need. While each framework has its own pros and cons, the macro benefits are the same. Among them:
- Reusability of code
- Maximum coverage
- Recovery scenario
- Low-cost maintenance
- Minimal manual intervention
- Easy reporting
Test Automation Strategy
There are some basic questions that you can ask as you formulate a test automation strategy. Based on the Roger L. Martin’s strategy framework published in Harvard Business Review, ask yourself the following questions:
- What are the goals of our team and broader organization? How can we measure our progress against these goals? For example, if a broad goal is to improve customer satisfaction on our app, how can test automation lead us to achieving this?
- With the options available to us, where will we choose to use test automation? For example, should we use automation to test certain user flows on our new app, yet still conduct traditional user interviews?
- In our chosen domain, how can delivering better software help us beat our competitors? How can we use software test automation to help us release better software?
- What software testing capabilities do we need to develop and maintain in order to outperform our competitors?
- What systems should we implement to maintain and build on these testing capabilities?
Who Should be Involved in Test Automation?
In short, domain experts. That’s why good chefs always taste their food before serving.
Would a CIO with little hands-on development experience be very effective in the position? Possibly not. By the same token, putting someone with no understanding of a technology’s users, the domain, and objectives in charge of its testing is a recipe for disaster. Instead, tests are often best designed by those with the best understanding of what and who the software is for. Again, that’s why test automation software that allows non-developers to create and execute tests should be an important deciding factor.
- Within the next four years, low-code and no-code application development will be responsible for more than 65% of app development activity.
- By 2024, 75% of large enterprises will be using at least four low-code development tools for both IT app development and citizen development initiatives.
Does this mean that traditional IT roles don’t have a seat at the test automation table? Of course not. But failing to involve domain experts early in the process can significantly curtail the project’s success.
Getting Started with Test Automation
So, you’re ready to give test automation a try? Consider the following steps to ensure sustained progress:
1. Start slowly. As mentioned above, companies often confuse automation success with large, complex frameworks and initiatives. Don’t make this mistake. Rather, build up slowly, analyze what worked and what didn’t, and apply these learnings as you go forward.
2. Don’t write your own test tools. To be blunt, this is a huge waste of time. With numerous products on the market, money and manpower could be better allocated to virtually any activity other than writing your own testing tools.
3. Manage it like a strategic initiative. So, if you avoid the above trap and invest in a test automation product, does that mean your work is done? Not exactly. Too many companies expect test automation to just magically happen, and neglect to manage it as they would another strategic initiative. To maximize results, treat test automation as a project with goals, scope, and clearly defined roles and responsibilities.
The test automation market is expected to reach nearly $110 billion by 2025. While this underscores the critical importance of automation testing, it also highlights how crowded the vendor landscape is. In order to reap the benefits of test automation, it’s essential that companies select the right partner who can address their current needs and scale to accommodate future testing requirements.
Through our AI-driven approach to test automation, Eggplant can:
- Expand automation beyond test execution, covering the full testing process
- Test real user journeys to optimize the customer experience
- Test any technology at every layer in any way
- Empower domain experts to become automation engineers
- Future-proof testing for the digital age
Learn more about how you can test smarter and other benefits of Eggplant’s intelligent approach to test automation.