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Software testing
Software testing
Automation testing, Manual testing, Startups
July 22, 2020
10 mins read
Thousands of lines of code, tons of data, catchy graphics, and months of hard work makes a perfect application! But what if the app doesn’t work under some conditions? What if it lags or is not able to meet the requirements of today for the client?
That’s why we have engineers as software testers who test the applications under every possible condition, remove the bugs and optimize it as much as possible.
Companies are spending millions of dollars on hiring software testers as the apps become more and more complicated. More the features, more the lines of codes, and thus more bugs and testing!
You cannot ignore testing because it tells you about the threshold and risks involved while running it, but can we make the task easier? Well! You might keep on thinking about it, and during that time, one can quickly test the software by AI. Yes, AI is the new boss!
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A process that takes weeks to complete and sometimes fails due to human error, AI will do that within hours and without any chances of error. Pushing the process of testing towards automation, AI is conquering every primary industry.
Gone are the days for resolving the bugs and issues quarterly or half-yearly. The need of the hour is ‘Continuous Testing’ which can be done only by Machine Learning and Artificial Intelligence. Developing a smart algorithm helps to find the maximum number of bugs in the least time with just one click.
Apart from the everyday challenges, the Internet of Things (IoT) is all set to enter the digital world and will surely attach to every significant appliance. Thus, with the increasing demand for IoT, more number of testers will be required who have to make sure that the solution is independent of the type of device.
Therefore, if we start preparing for the future technology as well, then we must start with adapting to the AI in software testing as well!
Though higher-order testing tasks may still be incomplete without human interference, functional testing of web and mobile applications, visual testing of user interfaces, auto-correcting element selectors, etc. can be done within minutes while humans might take days or weeks! But still, machines are being trained to solve higher-level order problems also.
It is moving towards the path of the open course community as well! Training data available on Kaggle can be used, and thus individuals can do the testing further easily!
With more and more data being generated, we can efficiently train the machines and apply smart algorithms. Companies are moving towards this practice because it saves their capital! As simple as that!
During testing, 80% of the task is to do a repetition of the checks that software already has while 20% is the tester’s creativity. Leaving this task to AI will eliminate almost all the bugs and leave the human resource with new development projects. Thus, corporates can focus on new ventures without missing out on the working of the previous apps.
Even experienced testers can’t eliminate all the bugs or think of the severe cases where code can fail. Manual testing has limitations, especially when the application has more than 1000+ users. With the help of automation, simulation of ‘n’ number of users becomes easy. It can be combined with a network, software, or web-based applications as well!
It is a well-known fact that Selenium, though used mostly while testing the UI, is quite unstable and sometimes tricky to maintain. So, while doing regular Selenium tests, AI can be used to feed the internal data having detailed information on web UI content, DOM elements attributes, locators, etc.
Many companies who have opted for AI software testing solutions have agreed that their team’s productivity has increased, production has boosted, which in turn helped in sales as well!
| Manual testing | AI testing |
| Manual testing is a linear process and sequentially takes place. | AI software testing is a quick process and takes place within minutes! |
| It takes a lot of time writing hundreds of test cases and executing them manually | AI bots produce hundreds of such test cases based on the client’s requirements. |
| A large number of humans are hired for manual testing | AI requires quite less human intervention. |
| There are always some amount of errors in the test cases. Production is quite less! | AI will perform every test accurately and provide feedback too! The production of these test cases takes place within hours! |
Different API calls have different fundamental patterns and relationships. Using AI, developers can create a series of API calls by finding common patterns among them. Those AI tools will further learn and update themselves.
If you know how irritating the “NoSuchElement Exception”, then automation is the only tool for you! AI solutions provide for self-healing tests. It means that AI bot will automatically detect the errors in the code and will fix them without any human intervention. For eg, if the developer changes the ID attribute, the UI Identifier will be corrected automatically in the test case.
JAVA developers very well know the hard is to start from a sparse JUnit Harness. Using AI, JAVA developers can do the testing with just one click.
What if every bug gets destroyed at the juncture of its production! Using smart ML algorithms, the system can learn from past trends and use the process of standard defect analysis, and bugs can be detected at the very first root!
Testim.io has embedded AI with Smart Locators to check hundreds of attributes and score them. One can easily customize coded tests in IDE. It also allows run browser tests on their grid or any Selenium-compatible grid.
It’s product AppvanceIQ is an AI-driven test automation system. It helps corporates achieve quality, performance, and security. It also allows organizations to become more agile and move faster to the cloud.
Test.ai helps to extend and integrate solutions with codeless test automation that won’t break whenever apps get an update.
To provide the feature of never breaking tests, Functionalize has multi-faceted ML algorithms support. The unique feature offered is the Functinize Test – cloud that gives you infinite test capacity.
One of those tools which made it to the list of Gartner’s report on Agile and DevOps. Their AI tool will automatically write unit tests for Java code. Diffblue helps in increasing developer productivity and removing the bottlenecks of testing. It also provides a free trial.
Sofy.ai gives the exclusive feature of validating your application by accessing the Android and iOS apps. Within a few minutes, you can create tests without any installation and coding.
Retest is an open-source tool in test automation. It is a fully functional free software testing API and CLI on Github and Maven Central. It also allows for data-independent test automation.
Applitools can easily replace brittle assertion code with a single visual AI-powered API call to stabilize the test automation. It also allows integration with storybooks along with automated visual testing into the CI/CD pipeline.
Mabl will enable the advanced feature of auto-healing and reliable tests that hello in the faster delivery of top-notch applications. It also has the option of integrated automated end-to-end testing into the CI/CD development cycle.
Eggplant unique feature is their automated feedback loops that suggest the changes required, detects the problems in business objectives, and helps them to delight the customers too! Other features include regression packs, bug hunting, and coverage analysis.
Summing up, we can say that AI will not only increase productivity but help the companies save on manual testing, provide better services and work on cutting-edge technology by investing the human resource on multiple new projects! This is the time when we learn to differentiate between smart work and hard work.
AI is soon going to become omnipresent and will have its utility everywhere. But that doesn’t mean there is no need for testing with AI. If the self-driving car’s intelligence does not work correctly, has no advantages, has poor response time, then it can inevitably lead to accidents or death further!
Thus, humans are still required for the testing of AI bots as well! So, a talented human resource combined with the upcoming technology can surely achieve any level of accuracy and reach the pinnacle of success!
We at RavStack have always believed in the power of AI, and our team also practices AI-powered testing. AI software testing has increased our DevOps productivity and increased our production. So, scale up your business with the power of AI. Contact us today for a callback from our software testing experts.
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Ravi is an out of the box thinker, mentor, advisor, and consultant to businesses, helping them in choosing the right technology partner. With more than 2 decades of work experience in global IT business, he possesses a talent for putting in place unique strategies and measures for streamlining operations, invigorating businesses, and heightening productivity.
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