How did software testing evolve?
In general, Software Testing has evolved over some time in the past few decades. In the 1980s and 1990s, when companies realized there should be a separate QA team to find Defects in software. An impression Developer would not like to present the Defect in later stages once the build is ready. Because the Developer would assume the software has been Built Perfectly by him. Then separate Software Testing QA jobs came into existence.
Testing was predominantly Manual Testing. And we didn’t have any such tools for Automation initially, and the Development Methodology was basically in waterfall Methodology. Where the developers worked for 6 to 8 months and finally made the product, and it fell into the hands of QA testers. Once the Tester finds any Bugs at a later stage, then send them back to the developers. And then the Dev Team has to fix that bug.
After fixing the same, they send it back for re-test again. It used to happen in the early stage of Software QA Testing. Or some companies still follow the same Waterfall model.
When did QA Automation Tools come?
In the late 1990s and early 2003s, Software Testing Services Companies started focusing on some software tools that could help testers perform software releases. Then QA automation tools came into existence to help the manual tester test on regression test cases and smoke testing.
It helps to automate the monotonous task for the testers used to do each time, and they can focus more on the functional test case for new functionality. So far, in last two decades, many automation tools have come into existence like Selenium, QTP, Winner, Test Complete, etc. And many people have got lots of opportunities in IT services Project base and Product Based companies. And they work in QA roles like Manual and Automation Testers.
Impact of Artificial Intelligence/Machine Learning in QA Jobs
Coming into the present age, and if we discuss future decades, AI (AI), Learning Machines, Data Science, and Robotic Process Automation are coming very fast and taking huge places in the Technology side and Software Industry. Many Experts are Predicting (that AI) and associated technologies are going to be present across many industries, with a good number of software packages that have more combinations of these technologies and are a part of our daily lives by 2020. As per some of the Expert reviews and Predictions, a few Jobs could also be less or seem to be invisible within the Future decades in the Software Market.
While coming to the QA part, some experts agree that there can be several cut-offs even in Software Testing QA jobs due to AI and related technologies. Some AI Tools will be coming into the Market & those AI Tools will soon start correcting code as the developers write it automatically. AI may come up with many more innovations in Testing, which would be much faster and much more accurate.
In the coming years, QA and Automated Testing will be more integrated using Machine Learning and AI. The main objective will be achieving Good Quality at Speed and faster resolutions. Many experiments are taking place in these AI / ML-related technologies to create faster and more accurate test framework architectures.
AI/ML Impacts on QA jobs
Some experts review that it could slow down QA opportunities in the manual as well as test automation industry. It is possible since AI Tools will be replacing much more Human intervention. Somehow, they may be correct but not completely. It’s not so easy to remove all human intervention, but yes, it will be less intervention. Because on the other side, some other Experts think there may be some Transitional Roles from Software Testing Professionals to Artificial Intelligence (AI) and Machine Learning (ML), Data Science related Products Testing Engineers. Testers have to upskill themselves in terms of Technology, learning about the same products.
There is a fear among QA professionals that AI/ML will replace their jobs soon. Instead of having that fear, QA professionals should focus on learning AI/ML/Data Science-related technologies, which can help them in the future to Test these particular related Applications. Some experts think a number of Jobs may come in the Future in QA with the Knowledge of these Products. Experts think AI will make it easy to perform testing jobs which will be good for QA professionals.
New Tools and Technologies May Come
With the help of AI/ML, some new Tools and Technologies can come into the market with Predictive Analysis, Robotic Automation, and cognitive solution, and the tester’s job will be easy. Once the developer writes code or if there is any change in application code. Artificial intelligence tools will be smart enough to read those particular steps automatically without any human intervention or rare human intervention. We can use this kind of ML-based tool for Regression Automation testing and Smoke testing.
When it comes to Artificial Intelligence & Machine learning technology in terms of Software Testing is more focused on creating and making the Software development lifecycle easier. Problem-solving and logic tools while AI / ML-related technologies can also help automate repetitive work and monotonous work in software projects of companies under the development and testing industries.
In the coming years, we are expecting many more inventions within this industry to deliver high-quality product releases. IT services have already started the transformation using these technologies in testing automation and creating Hybrid applications.
It will make it easy to understand client requirements
Machine learning and Artificial Intelligence can also be used in understanding, Predicting, and forecasting client requirements. The correctness of client requirements can change in the testing process and help testers analyze the customer data. Predictive analysis will give more information and inputs on the company’s product features as they need them.
Still, Machine learning and Artificial Intelligence should not be considered a hazard to software testing jobs. Testers can look into the advancement of Technologies to grasp and learn the same.