There was a time when companies were hesitant to deploy automation as they feared venturing into something they didn’t fully understand. But now, automation technology has become the norm, and hyperautomation is enabling businesses to change their ways to a more people-centric approach.
In modern software development, testers work in compressed cycles, and automate regression tests to save costs, time and effort. Insprint test automation provides an ideal development scenario, wherein, the entire process from creation to implementation and performance reporting of a software product happens in one sprint.
In quality assurance, automation testing is one of the quickest and the most effective methods for checking the efficacy of software or an application. However, like most processes, be it a company’s business model, or the software development practices, automation testing has its own set of limitations.
There’s no doubt that automation testing is the quickest and most cost-effective method of QA testing. However, it cannot do everything, since some limitations of automation testing are built into the system and must be balanced against manual testing, while some are the result of inexact pre-programming, such as a failure to develop effective automation test hooks.
Let's look at some of the drawbacks of automation testing:
The use of AI in software testing is geared towards making the software development lifecycle easier. Through the application of reasoning, problem solving and machine learning, artificial intelligence can be used to reduce the tedious and manual aspects of software development and testing, and automate the whole process.
What is automation testing?
Automation testing is the software testing process of running test cases by using automated testing tools. With this type of testing, QA teams can perform tests faster, receive more accurate results and address code defects sooner.