Machine Learning And Its Impact On Software Testing

In today’s world customers are more towards digital world than ever before. Everyone is now expecting more from technology and want greater benefits. On-going example is voice based search like SIR> voice based search is increasing day by day and now software developers are building apps that is having the fear tire of voice search.

Likewise, software test led chat bots are now excessively used to handle customer facing service inquiries and online sales. By using the latest technology that is AI and machine learning, several companies are moving ahead in order to enhance their user experience and maintain the product offerings in order to increase their productivity.

According to me one method is to analyze what extra benefits a customer might need on the basis of previous given data. There are several techniques in which predictive analysis is being done.

The IoT, which is soon-to-be running on 5G networks, is a good example of complex systems with collectively huge processing requirements. And in coming days traditional automation testing methods is going to hold back as they provide delays and bad user experience and we knows user experience is the main thing that needs to consider.

Rather than this, intelligence is being programmed into the network proficient of delivering real-time perceptions, replying to developing traffic levels and enhancing the system as a whole.

Machine Learning in “Software Testing” can help prevent some of the following but not limited cases:

1. Saving time on Manual testers of writing test cases and other work related to manual testing

2. Test cases are brittle so when something goes wrong a framework is most likely to either drop the testing at that point or to skip some steps which may result in wrong / failed result.

3. Tests are not validated until and unless that test is run. So, if a script is written to check for an “OK” button then we wouldn’t know about its existence until we run the test.

Why do we Need AI in Software Testing?

We all knows that software testing plays an important role in the development sector. But, several times software developers are not able to carry out a comprehensive testing of a web application due to time shortage and resources also. In such circumstances there is a need of system that defines everything in an intelligent manner and focused responsiveness from the phases that could be handled through automation based on repetitive patterns.

And according to expert’s reports, software testing generally takes the most time and resources and capital also. So, AI is the best way to proceed with as this is going to help developers to focus effectively on their work.

As 75% of software testing is just a regression testing (means repetitive checking), AI plays better role here in order to automate the test cases repeatedly with effectiveness rather than using a software tester which might increases costs of the projects.

And I think it is going to be a better practice if the AI and efforts used in recognizing the web apps problems by developing distinctive and innovative test environments. So, it is perfect to leave the repetitive work to the artificial intelligence automation which is going to leave only 18% of the software testing ops to the software testers and reasoning capabilities.

And manual testing is going to face scalability matters, wanting the management of various machines to run. With corporations waking up to machine learning, software developers are seeing it to simplify decision making, drive automation and increase effectiveness in the area of testing.

By applying AI algorithms, the testing industry is going to be more effective in case of building productive software for the consumer and understanding their behaviour. But it is also important to use AI techniques effectively by following AI algorithms in a proper way. By implementing the smart algorithms testers are going to detect maximum number of bugs.

Hope you enjoy this article!!