Artificial Intelligence : Solution for Effective Software Usability Testing

Artificial Intelligence in Software Testing

The complexity in technology and its fast-paced growth make enterprises think out of the box and gain an advantage by launching new products in record time. Software testing is a necessary process which ensures that quality products are delivered to the customers and also safeguards against potential failure. However, time management and the right technology are the key towards becoming the leaders in a market. AI’s ability to think, learn, handle errors and draw a conclusion is the ultimate solution to all the testing woes. 

Role of Artificial Intelligence in Software Usability Testing

Automated Test Case Writing

A test case is a set of variables that demonstrates or determines whether the software has the desired capability and functions correctly. Test Case allows a tester to understand through different ways of validating features and ensure that no key functionality is missed out in the process. Even negative test cases are documented, overlooked and referred in the future. 

Automation of test case writing will reduce the possibility of error when it is written manually, improving precision. Automation can allow the tester to get rid of the incorrect test case and improve the unit test (testing an individual unit or component of a software). The AI-powered unit test detects problems effectively, allowing the developer to fix it before it reaches the customer.

Improved Precision & Defect Tracking

Making mistakes is one of the most common human tendencies. The most skillful tester is bound to make errors while doing manual testing. But AI is more precise and eliminates the possibilities of error by analyzing the data and performing the task with more accuracy.  

Identifying bugs and fixing them on time saves the software from being a failure and improves its quality before it reaches the market. Artificial Intelligence software enables better defect tracking in a matter of seconds. AI algorithms have changed the way bugs are fixed during software usability testing. It identifies the code line with the error and changes the code by itself or assigns the bug tracking to Quality Assurance (QA) teams. 

Time Management

Source code gets modified by repeated software tests. However, manually repeating this test is a time-consuming and expensive process. AI-powered automated testing can be replicated repeatedly without any additional cost with a much quicker pace and precision. AI can simulate thousands of testing’s in a short period reducing it from days to mere hours. 

Since time is considered directly proportional to money, reducing the time consumption will translate directly into cost savings. With continuous growth in AI technology, it will be interesting to see the improvement in time and cost management in the upcoming years. 

Expanded Test Coverage

Test coverage enables to gather information, identifies test cases that are meaningless and creates additional test cases to increase coverage. It ensures the test quality by determining all the decision points and paths that can increase the test coverage. 

Leveraging AI in software testing will quickly identify the uncovered code, analyze it and add new test cases. It can check memory, internal program states, data tables and file storage to determine if the software behaves as per expected results. AI testing software can perform more than 1000 test cases in a single test, which is impossible with the manual test, overall expanding coverage, and improved software quality. 

Evolution of Bots

Bots increase the depth and scope of testing by reducing errors and working more accurately. AI bots evolve and learn new application function with the change in codes. 

When a developer makes changes in a code, AI bots quickly detect these changes and analyze it. Then it tries to determine whether this change is related to any new functionality. If so, it runs test for this new functionality and also notifies the Quality Assurance (QA) tester and developer if it fails. Evolution of bots ensures the quality of the product.

Conclusion

The competition to become the leaders in the market has driven the enterprises to demand weekly product launches. With the tightening deadlines and high expectations, the development team no more enjoys the luxury of time. The only solution is to test faster and smarter, leveraging the power of Artificial Intelligence. 

According to Fei-Fei Li, a Chinese-born American computer scientist and writer,

“The tools and technologies we have developed are the first few drops of water in the vast ocean of what AI can do”. 

Becoming the early adopter is crucial to ensure effectiveness in high-velocity software rollouts, ultimately resulting in superior business outcomes.

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