AI (Artificial Intelligence) has transformed many sectors, including healthcare, logistics, transport, retail, and customer services. But soon, it’s expected that AI will be omnipresent in every area in the form of innovative technology, including software testing.
If we were to talk about AI technology in testing, then it’s fair to say that AI has made testing smarter and more accessible. The traditional approach of testing has its own set of challenges; however, the use of AI technology can help overcome them and make the process automated and less-tedious.
Testers can leverage artificial intelligence and machine learning to optimize their automation strategies, adapt faster, and operate more effectively.
In this article, we’re going to discuss traditional testing, its challenges, and why we need AI in software testing. Along the way, we’ll highlight some points that direct how AI renews the world of testing.
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Traditional Testing & Its Challenges
The traditional testing approach requires the tester to perform in a phased manner simply. It usually includes checking a set of tasks that collectively form the overall project. This approach helps validate the quality of the product; however, there’s the catch. Traditional testing makes it difficult to implement changes in the software.
Testers need to go through every step to check every smallest to the most significant element of AUT, and it’s undeniably time-consuming for both software testers and clients.
In the beginning, this approach may seem more straightforward, but it can be more challenging when the AUT is complex.
Moreover, this situation gets difficult since the traditional approach only checks the specific cases chosen by the tester.
Why do we need AI in software testing?
Software testing is a process that is all about preventing defects and maintaining superior quality while developing software. In previous times, testing was a difficult task for sure, but with the advent of AI, it’s possible to quickly and efficiently build error-free applications.
Earlier, test automation required manual work to write and execute test codes, but AI can do this automatically. Also, it continuously improves as it learns from human inputs.
This new technology will enable every team member to have access to a virtual test team along with speed, scalability, and intelligence than the traditional testing approach.
Here’s a Quick Overview of Traditional Testing vs. AI for Software Testing
Maintenance Cost: In the traditional testing approach, maintenance is the hidden cost. Due to the app changes, the test code often is updated. Hard-coded test scripts are brittle and can be used only once, and hence, this traditional technique costs a fortune.
On the other hand, AI bots are not hard-coded and automatically discover new features and evaluate the latest changes to determine if they are features of bugs. It’s safe to say that AI bots thrive on change.
This is the same reason why traditional testing is not a scalable option. On the contrary, an AI-based testing approach can generate thousands of test cases in a matter of minutes.
How AI Remodels Software Testing
1. Advancing manual testing & the entire process
AI-powered algorithms can write their code and can be leveraged for maintenance and test execution. Therefore, it makes regression testing faster, smarter, and better.
When a tester deals with thousands or even millions of code lines, testing can be confusing and take many days, weeks, or months to get through. In reality, even if you hire the best software testers, manual testing takes time.
AI can write scripts, analyze a significant amount of data sets, and accelerate the entire testing process. This technology will help you by integrating itself in the early stages of mobile application development services.
2. Reduces maintenance & eradicates flaky tests
With the AI-based testing approach, the possibilities of streamlining the testing process have magnified. This is because AI uses a set of algorithms to identify errors through automated testing. To put it another way, AI has a self-healing mechanism, which can detect and fix problems in failed tests before they occur.
It is also capable of figuring out which tests are stable or flaky and examine what tests need to be modified to ensure test runs are steady.
The use of AI in software testing can optimize the wait times used in tests to wait for the pages to load. Based on large numbers of test runs, it can also handle tests running on different resolutions.
3. Eliminates more bugs
Enterprises have been continuously looking for fast delivery and businesses for rapid software testing over many years. Thankfully, they’ve found the answer in the form of an AI-based testing approach.
Earlier, when bugs were identified, experienced testers had wondered how it went unnoticed while doing manual testing. With the use of AI, the questions like when, why, and where will be buried. Testers can get detailed information on every bug during the cycle automatically.
As a side note, no matter how organizations are actively following test automation best practices and implementing them, AI technology prevents your organizations from hassles while testing.
4. Speeds up timelines
Is going through hundreds of thousands of lines of codes easy for manual testers? Absolutely not.
AI can do wonders in software testing as it can quickly go through log files, scan code in minimal time, and detect errors in much lesser time. Hence, you will get more accurate results. With this technology’s help, you can focus on crucial parts of the software development or pay attention to testing new features.
5. Automation the testing process
The significant role of QA’s job is to ensure that the new codes would not destabilize the existing functional code. Development and addition of more and more features can overwhelm and burden software testers. But there is a way for testers, using AI bots, which enables them to evolve with the changes in the code.
AI bots can identify a modification to the code and be programmed to decide if it’s a new feature or some defects due to the codes’ changes.
Automation testing can be improved by investing in a software testing platform, such as BrowserStack, which enables developers to test their websites and mobile apps across on-demand browsers, without requiring users to install an internal lab of virtual devices.
6. Enhances Accuracy
While DevOps and Agile have changed the way of QA services, Artificial Intelligence has raised the expectations of several software testing companies. The reason for the popularity behind AI in software testing is it enhances the speed, accuracy, and efficiency of applications and software.
Also, AI is responsible for substantially eliminating the probability of human errors and shortening the time to run a test. Above all, it increases the possibility of finding bugs or flaws.
Conclusion
This omnipresent technology AI will undoubtedly help make the lives of testers easier by detecting bugs quicker and faster. With speed and accuracy, AI expands the testers’ horizons to write better test scripts, create testing methods, and build the best possible user experience.
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