What is the future of software testing in the era of artificial intelligence and machine learning?
Artificial intelligence (AI) and machine learning (ML) have become the integral part of our daily lives. Drones, smartphones, etc.; are some of the examples of AI use in our everyday life.
Now when we are continuously using AI and ML in our daily lives, what will be the role of AI and ML in software testing?
Software development lifecycle is getting daunting every day. While delivery time is getting shorter, software testers need to share their feedback with developers instantly.
The pace at which software are being launched, you are left with no choices than to continuously adapt yourself to the changing scenario.
Here comes new age testing
After the entry of AI and ML, software testing will become both easy and quick. AI by using ML can write its own code and can also be used for test execution and maintenance.
With the introduction of AI/ML in testing, test automation and regression testing will become quick and smart. Testers can stop worrying about mundane tasks and can focus on important strategies.
Will ML and AI make software testing less important?
No, ML and AI will not make software testing less important. In fact, it will only get better with AI and ML. It will help in quick identification of bugs. Instead of having apprehensions, software testers should work towards incorporating ML and AI in software testing.
For instance, a company prefers ML and AI over human beings. Though they will get precise results, they will lack some crucial aspects like performance, scalability, documentation and security, which can be given only by humans.
Therefore, it will be wrong to say that AI and ML will make software testing less important.
Impact of ML and AI in software testing
The speed at which companies want to launch their software in the market is high. The main reason behind this surge is stiff competition in the market. Thus, there is a need for software to be developed and tested swiftly. Below are some of the changes which one can expect to witness in software testing due to ML and AI:
- Improve accuracy: Even the most meticulous tester can also commit mistakes while carrying out repetitive manual testing. It is where automated testing can help by performing the same steps accurately over the period of time. It helps in saving time and ensures the accuracy as well. When testers don’t do manual testing, they can devote more time towards creating new automated software tests.
- Going beyond human limitations: It is tough for QA (quality assurance) departments to efficiently execute a controlled web application test with more than 1000 users. However, ML and AI in QA can address this issue.
- Expedite product launch: Every time there is a modification in code, software testing needs to be done. However, repeating those tasks manually is tiresome and costly. In contrast, once created, it is feasible to execute automated tests again and again at a fast pace and that too without incurring an additional cost. Thus, ML and AI in QA expedite the product launch.
ML and AI have shown their capabilities to the work. By using ML and AI in QA, companies can easily save both their time and money. While the present looks good, the future is exciting. However, it is essential to be cautious while developing ML and AI for advanced stages to ensure the existence of humans along with them. Backed with ML and AI, software testing will only get better with time.