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.
The stats don’t lie: mobile devices account for half of web page views around the world. This shouldn’t surprise us, since more than 75% of Americans own a smartphone with one in five American adults opting for a smartphone-only lifestyle.
That’s why product developers are adopting a mobile-first strategy. And since Android dominates the mobile OS market, it only makes sense for QA testers to become fluent in Google’s digital language.
SaaS platforms have been on the rise for some time now. From professional endeavors to leisure activities, more of our experiences are shifting towards a virtual delivery. And because immediate access from any location makes the shortlist for any software system, consumers often choose SaaS applications over on premise software systems.