How Machine Learning Can Transform A Software Tester’s KRA

Image © Image Source: Twitter -@darktelecom


Image Source: Twitter – @darktelecom

Technology through the years have evolved significantly, and today it is such a stage that every business nowadays is relying on it for almost every job. However, to keep the good work going, technology always needs to be updated with time in order to make its customers stay.

In this scenario, software testing plays a vital role as it decides what software ought to work better and succeed, and finds faults in software prior to any third party individual. To be exact, Software Testing is a process of verifying a computer program and make sure that it meets the specified requirements and also delivers the desired results. As a result, you identify bugs in software product/project.


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With time, this field of software testing is just getting broader and today, the industry is also realizing that testing is more important than programming. It is also prophesied that testers are soon going to spend more time and their resources on testing mobile and hybrid applications, and the time spent on actual development is going to shrink. Also, it requires a huge budget for tools and resources in order to make software flawless. And this snowballing significance of testing is making organisations across the world to look for the best talents as at present,  testing a written code is not enough.

The Challenges

There was a time when software testing used to be a simple and straightforward task — the tester would enter input and compare the results with the expectations. It is without a doubt is one of the most peaceful things when you have a system that tests the application — one can run the same tests again and again on every release. However, things have changed; today, it is not that easy and relieving the way it sounds. There is a tremendous amount of data that testers need to handle in a limited period of time, and it eliminates the efficiency of traditional testing and therefore it requires new approaches. 

Another challenge is that nowadays it is becoming more critical for every organisation to maintain the standard of their applications — whether its PC or Mobile. And as a result, the releases have started come more often than ever before. And this is making the job of a software tester swampier.

Therefore, in order to make software testing efficient and smarter, machine learning and artificial intelligence seem to be a good choice.

There is no denying to the fact that ML and AI are playing vital roles in all walks of life. But, how will intelligence influence software testing? How will they actually enhance it? Read along to find out!

This Is How ML Can Help In Software Quality Assurance

Reduce Error

Traditional software testing depends on humans and there are instances when humans have proved that they are quite prone to making poor assumptions. If the time to handle data is less for a tester than there are chances that they will deliver skewed results, and no company would want their consumer to spot a bug that leads to escalation. This is where ML comes to the rescue — it can handle tons of complex information and find patterns that are predictable, and then alert the tester about those differences.

That is not all, it even learns from the previous tests and applies that knowledge in future tests to help the tester deliver more accurate results.

Automate Test

Suppose you write code that tests the application, and now you can run the same tests again and again on every release using that code. But what if your tests fail due to developers making changes to your application?

Machine learning is the key to dealing with such a situation. When you have a tool that uses ML, you don’t have to keep making changes to your code that tests application — the ML-based system will automatically adjust to the changes made by the developers, making your tests more maintainable and reliable.

Human Tendency: Let’s Get Worried About “What If These Technology Eat Up Our Jobs”

Machine learning might be doing most of the work, but it won’t replace humans from software testing as it is here only to help. Also, testing is not the only thing that covers the entire software quality area, testers and QA teams are also supposed to spend their time figuring out the types of tests to carry and ensure the quality of a software.

Therefore, don’t worry when a new technology is introduced to a field of work. And in the case of software testing, ML will solve the pain-points in traditional testing and make the software testing process more efficient and relevant.

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Harshajit Sarmah
Harshajit is a writer / blogger / vlogger. A passionate music lover whose talents range from dance to video making to cooking. Football runs in his blood. Like literally! He is also a self-proclaimed technician and likes repairing and fixing stuff. When he is not writing or making videos, you can find him reading books/blogs or watching videos that motivate him or teaches him new things.

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