How Can AI Influence Software Testing?
AI is currently overwhelming almost all the industries on a global scale. Software testing is not an exception to the rule. However, many professionals still underestimate the influence of artificial intelligence on the IT sector. What is AI testing and how can it affect the QA process? Which AI solutions for testing will provide the best value for your organization? Learn more about the impact AI technologies can cause to digital testing in the nearest future.
AI and Software testing: the prognosis
AI, that is also called ‘machine learning’ by many experts, is the ability of automated technologies to “self-educate” and become more developed while being in progress. Each time a certain algorithm works out its function, it becomes smarter and more effective. In the testing area, a certain kind of AI becomes better after performing each test case. But, why do human testing still remains to have a higher value? Why does machine learning fail to replace human QAs? Can various types of testing come hand in hand in one QA process?
The question about the changes AI can cause to the world of testing remains to be answered. However, we can still make a smart prediction on how the functionality testing and mobile usability testing will be changed due to the newest technologies.
Accelerating the process of manual testing. Currently, manual testing is still one of the most significant parts of numerous QA processes. It requires lots of time and human resources for getting the best results. However, with the help of AI, manual testing is likely to lose its popularity, as well as it will be drastically speeded up. For example, AI is likely to soon be able to sort log files and make the job of QA less routine and much more effective.
Identify a larger number of bugs. Automation testing can find various bugs on different stages of testing. However, AI is likely to have even richer tools and options. It is likely to be able to find, identify, and save the information about the bug or crash in a certain program up to seconds. Not only the more data about the bugs the technology can offer, but it might also be able to find more bugs traditional testing methods still fail to identify. This way, AI is likely to improve the quality of testing, reporting about more bugs that require fixing.
Make the QA process more automated. AI can find new pieces of code automatically and check how they fit the overall program’s performance. Does the new code fit the new release? Does it have any defects or bugs? AI is likely to perform automated tests with no need to restart the QA process after the new changes have made. This solution will make an automated QA process faster and simpler. The bots will be also able to modify themselves according to the changes made in the testing program.
Make predictions. AI is not only about checking bugs and errors. It is likely to provide predictions about the user’s behavior and preferences. This feature can help developers make their apps more user-friendly and meet the user’s expectations with almost no efforts. Analyzing the user’s data also allows creating more advanced scenarios of various games and apps. In case users get more personalized digital solutions, it usually improves their product satisfaction levels.
Create new tests automatically. Since AI is a flexible and smart technology, it might be soon able to create its own tests. For example, it might be soon able to generate codes that are responsible for pressing different buttons, filling forms or performing various basic functions. Human testers will get their job significantly simplified because of the digitalization of most QA processes.
Eliminate the risks of serious crashes. The AI solution might become a bodyguard for your program. It might be constantly analyzing the appearance of various risks or the interference of third parties to the program code. In case something suspicious occurs, the AI can automatically block the threat or report about the issue. If it is able to protect your program from malware or other types of attacks with no need to address the problem to the human tester, the AI solutions might also become the advanced antiviruses.
Analyze business performance. Being an excellent prediction solution, AI can analyze various factors that have the most vital impact on the overall success of the app. This includes conversion rates, load time, and other indicators. With the help of artificial intelligence, the business owners will be able to predict the key parameters of the business performance before launching the product. The technology will also identify the weakest points of the digital product and provide a few solutions on how to solve the most serious problems on the fly. Improving the business performance of any application will be much easier and less complicated.
Reduce costs for testing. Since AI can optimize codes, reduce the volume of manual testing, identify more bugs, and eliminate the risks of crashes, it is likely to involve fewer human testing. Artificial intelligence can combine various types of testing in a single QA process, making the management of the testing procedures easier. In other words, the QA process can become cheaper and simpler (if we can solve the higher costs of the AI solution itself).
Bring new tools to crowdsourced testing. Crowdsourced testing is likely to be influenced by the AI too. The testers are able to provide more quality testing with the help of the innovative tools powered by artificial technology.
What are the drawbacks of using AI in software testing?
However, AI in software testing still has lots of drawbacks. First, the most effective machine learning technologies are incredibly expensive. Therefore, many companies find using AI in each QA process unaffordable. Each new product or service, developed by the company, will require a new AI solution to fit its needs. In this case, the testing process might become even more pricey than the overall process of web development. The expenses are likely to become too high for some companies.
Second, the current AI market lacks effective and universal testing solutions. You can’t find a tool that will do the entire testing for you or substitute human QAs. Real testing experts will still manage the technology and be the head of any successful QA process.
Third, AI is not able to think like a human. You will get no innovation, out of the box solutions, new concepts or great ideas in case you choose only machine learning testing tools. Only human tester can effectively operate and lead the process of testing.
Generally, AI in testing is a promising technology but it is still not able to replace a human tester. Human QAs remain to be the kings of the testing process, no matter how smart your testing technology is. So, the most win-win combination for any company is to use both AI and human testers for getting the best results.
By the way, Ubertesters is one of the companies that value most the newest tools for various types of testing. With the help of our services, you will be able to get an excellent product using a unique platform for testing or crowdtesters upon your request. In case you need professional assistance in performing quality tests or require some advice about QA tools or service, don’t hesitate to contact us email@example.com.