5 Advantages of Autonomous Testing

Anushree Chatterjee

Autonomous testing is every tester’s dream. The system takes care of everything, allowing humans to take a breather.

Technologies like AI, NLP, ML, and more take care of various aspects of software testing, such as test case creation, test execution, test maintenance, and test reporting. Sounds too good to be true, right? But it is becoming a tangible dream with each passing day. In fact, it is also becoming a necessity. As applications become more complex and development cycles get shorter, traditional testing methods can struggle to keep up with frequent releases and continuous updates.

With autonomous testing, organizations can automate several activities that traditionally require significant manual effort, including test creation, execution, maintenance, and result analysis. This helps teams identify problems earlier, reduce repetitive work, and maintain software quality throughout the development lifecycle.

Traditional Automation vs. Autonomous Testing

We may not have the perfect tool that offers complete autonomy, but we do have close seconds that automate various aspects of software testing.

The main reason why the testing community is striving to build autonomous testing systems is due to their advantages.

Advantage #1: Test Continuously and Frequently

If the system automates test creation, execution, and reporting for you, then it is a no-brainer that the process will be faster compared to a human doing all of it. This means that you need not wait to test the application before certain events like releases or go-lives. Instead, you can make it an ongoing process where testing takes place, like one of those activities that your schedules frequently include, and allow it to happen in the background.

For example, imagine an e-commerce platform that undergoes frequent updates to introduce new features, improve user experience, and fix bugs. A critical component is the checkout process, which involves multiple steps and interactions.

If testing is performed only at specific intervals, such as before a major release, a critical bug in the checkout process might go unnoticed until the final stages of development. This could result in significant delays, financial losses due to lost sales, and damage to the company’s reputation.

Autonomous testing automates tests that cover various checkout scenarios and runs them with every code change so issues can be identified and addressed promptly. Tests can be triggered whenever developers introduce code changes, merge pull requests, or deploy new builds. This provides quicker feedback and helps teams identify problems while the changes are still fresh. For example, a change in the payment gateway integration might introduce a bug that prevents successful order completion. Continuous testing would quickly flag this issue, allowing developers to fix it before it impacts customers.

You can further integrate with CI/CD pipelines for real-time feedback on code changes.

Advantage #2: Detect Defects Early

The result of continuous and frequent testing is the ability to detect defects early on in the software testing lifecycle. One of the biggest advantages of finding defects early is that developers can address them before they affect other parts of the application. A defect discovered during development is generally easier to investigate because the code changes responsible for it are still recent.

Let’s say a defect was detected in the development environment; fixing it is going to be easy and painless. Instead, if the same defect went undetected and was found by the customer in production, then you can imagine the efforts that will go into not only fixing this issue but also managing the application version that exists in production and is used by so many.

For example, consider a financial application that calculates interest rates based on various factors. A small change in the formula is introduced. Without early defect detection, this change might go unnoticed until the application is in production. If the error results in incorrect interest rate calculations, it could lead to significant financial losses for the bank and its customers, damage to the bank’s reputation, and regulatory issues. Read: Automated Testing in the Financial Sector: Challenges and Solutions.

Autonomous testing allows early defect detection. It would continuously monitor the codebase and execute relevant test cases. As soon as the change is introduced, the testing system would identify the error in the interest rate calculation. This allows developers to rectify the issue immediately, preventing it from reaching production and causing financial and reputational damage.

Advantage #3: Improve Testing Speed and Efficiency

Another important benefit is the ability to handle large testing workloads more efficiently. As applications grow, the number of test scenarios also increases. Executing every test manually after each update can become a bottleneck for development teams. Autonomous testing can execute test cases and analyze results much faster than traditional manual or scripted testing methods. Moreover, since the system takes care of everything, you need not intervene unless necessary, such as to check the reports.

For example, consider a large-scale software project with thousands of test cases. Manually executing and analyzing these tests would be extremely time-consuming and prone to human error. A lengthy testing cycle can delay the software release, impacting revenue and market share. Additionally, manual testing is susceptible to human error, leading to missed defects and potential quality issues.

Autonomous testing can execute hundreds or even thousands of test cases simultaneously, providing rapid feedback on code changes. This accelerated testing process allows the team to quickly identify and fix issues, preventing delays and ensuring software quality.

Read more about Test Scalability.

Advantage #4: Reduce Testing Costs

The cost savings associated with autonomous testing go beyond reducing manual testing effort. Organizations can also reduce the time spent writing automation scripts, maintaining test cases, investigating repetitive failures, and performing regression testing.

In addition to this, reducing the need for extensive manual testing and autonomous testing will lower labor costs. Moreover, early detection of defects reduces the cost associated with fixing bugs later in the development cycle.

Consider an organization that releases software updates every week. Its QA team may need to execute the same regression scenarios repeatedly while also checking newly introduced functionality. As the application grows, maintaining these tests can consume a considerable amount of time.

By automating more of these activities, the organization can reduce repetitive work and make better use of its existing testing infrastructure.

There can also be indirect savings. Finding defects before deployment reduces the likelihood of expensive production fixes, emergency patches, customer complaints, and service disruptions.

Advantage #5: Make Better Use of Testing Resources

Software testers bring valuable knowledge about application behavior, business requirements, and potential user problems. However, when a large part of their working day goes into repetitive regression testing, they have less time to investigate complex scenarios.

For example, think of a software development team with a limited number of experienced testers. Manually performing regression testing on a complex application is time-consuming and requires significant human effort. The team might struggle to meet testing deadlines, leading to delays in product releases and increased costs.

Instead of spending hours repeatedly checking whether the login functionality works, testers can investigate less common scenarios, such as simultaneous login attempts, unusual authentication failures, or unexpected session behavior. This makes better use of testing expertise and helps improve overall software quality.

Autonomous testing can handle the execution of repetitive test cases, freeing up testers to focus on complex test scenarios, exploratory testing, and test case design. This efficient allocation of resources improves overall test coverage, accelerates the testing process, and enhances the quality of the software product.

Some More Advantages of Autonomous Testing

• Better adaptability: Autonomous testing systems can quickly adapt to changes in the application under test, such as new features or updates. This keeps the testing relevant and effective even as the application evolves.
• Better accuracy and consistency: Running tests over and over again is easier on a machine. Moreover, you’re going to get consistent results because autonomous testing ensures that the system adapts to code changes. The AI models are trained to determine what is an issue and what isn’t. This will give you dependable results.
• Good test coverage with AI: Autonomous systems are trained to analyze multiple aspects like code, requirements, historical data, and bug reports. They can create and execute a broader range of test cases, including edge cases that might be overlooked by human testers. It is definitely less resource-intensive for the system to do this research and test creation than for a human.
• Easy scaling: Autonomous testing systems can easily scale to handle larger and more complex applications. They can manage the increased load without a proportional increase in manual testing efforts.
• Reduced test maintenance effort: With AI in the picture, autonomous testing can help reduce test maintenance. Self-healing is a powerful capability that helps tools learn from errors and rectify the scripts. This reduces the amount of manual script maintenance required and helps teams spend more time on actual testing.
• Maintain consistent test execution: The repeatability involved in autonomous testing is helpful when one has to test the same scenarios over and over again.

Issues You Can Avoid Through Autonomous Testing

• Regression failures: Changes to one application component can affect existing functionality. Regular automated regression testing helps identify these issues before release.
• Missed edge cases: Testing only common user journeys can leave unusual but important scenarios untested. AI-assisted test generation can help identify additional cases.
• Automation maintenance overhead: Script-based tests may require frequent updates when application elements or workflows change. Self-healing capabilities can reduce some of this maintenance.
• Delayed feedback: When testing happens only at specific milestones, developers may discover defects late. Continuous test execution helps provide feedback earlier.
• Testing bottlenecks: Large regression suites can slow down release cycles. Automated execution and parallelization can help reduce waiting time.
• Financial loss: Fixing issues found in higher environments like production will prove costlier than fixing the same issue in a development environment. The loss doesn’t stop there, though. Imagine if a major retailer failed to identify a critical bug in their checkout process until after a major marketing campaign. This will result in lost sales, customer dissatisfaction, and damage to the company’s reputation.
• Reputation damage: A business’s reputation is everything. Imagine if a major outage occurred due to a software error that went undetected in testing. This would result in widespread user frustration and negative publicity for the platform, which could not only lead to financial losses but also drive away customers.
• Delayed time-to-market: In this fast-paced world, timely product launches are everything to keep customers hooked. So, if a major software product is delayed due to the discovery of critical bugs late in the development cycle, it will result in missed market opportunities and increased development costs.
• Increased support costs: A software application with numerous undetected bugs will lead to a surge in customer support inquiries, increasing operational costs.
• Customer dissatisfaction: Working with a glitchy application is a pain. With so many alternatives available in the market today, keeping the loyalty of your users has become increasingly difficult. Thus, fewer defects mean a better user experience, meaning users are using your application.
• Losing valuable resources: Time and effort aren’t the only resources lost. You’ll frustrate and tire your team members, pushing them to consider other alternatives. Testers can focus on higher-value activities.
• Poor job satisfaction: This is one of the downsides of doing repetitive tasks manually. If autonomous testing takes off the load, then testers can focus on challenging and rewarding tasks.

Autonomous Testing with testRigor

If you are looking for autonomous testing, testRigor is the closest thing to it.

• Plain English language testing: testRigor records test scripts in plain English, similar to how human testers would write manual test cases. That’s not all. You can make the process autonomous by using the generative AI capabilities of this tool to create tests. Provide a thorough description of the application and watch testRigor create a series of test cases in plain English for you. You can use this as a base, if not the final test case, and modify the test manually as required and add more tests to the suite. Besides this, you can manually add tests to the suite or use the record-and-playback feature to do so.
• Stable and reliable test runs: Running tests in testRigor is hassle-free, as the AI engine ensures that tests run despite changing environments and applications.
• Self-healing and visual regression: This AI tool can also identify changes in the application under test and suggest them to you. testRigor can easily handle UI changes, like a button’s label or position changing, as it visually assesses the application to see if it is still the same element the test case is talking about.
• Verifies modern applications: testRigor can handle modern applications with AI features like chatbots and dynamic images like graphs.
• Supports a variety of platforms: With testRigor, you can validate applications across platforms like web, mobile, desktop, mainframes, APIs, chatbots, AI apps, and more.

There’s a lot more you can do with testRigor. Check out the complete list of capabilities and testRigor’s benefits.

Frequently Asked Questions (FAQs)

• What are the main advantages of autonomous testing?
  The main advantages of autonomous testing include faster test execution, early defect detection, reduced test maintenance, improved test coverage, lower testing overhead, and better resource utilization. It also helps teams adapt testing activities as applications change.
• Can autonomous testing reduce test maintenance?
  Yes. Autonomous testing tools with self-healing capabilities can recognize certain application changes and adjust test interactions. This reduces the need for manual script updates, although human review may still be necessary.
• Does autonomous testing eliminate the need for manual testers?
  No. Autonomous testing reduces repetitive testing work but does not eliminate the need for human expertise. Testers are still important for exploratory testing, validating business requirements, assessing risks, and investigating complex application behavior.

“We spent so much time on maintenance when using Selenium, and we spend nearly zero time with maintenance using testRigor.”

Keith Powe VP Of Engineering - IDT