The platform of Artificial Intelligence (AI) and Machine Learning (ML) has been considered a highly productive domain by organizations worldwide. With the advent of AI testing, the software testing realm will eventually witness a monumental shift in the way testing activities are carried out. Accurate test results along with testing large amounts of data without any human intervention can be made possible by the AI platform. A QA tester has to raise the bar in terms of upgrading the specific skillsets required to manage the complex and intricate aspects of artificial intelligence and machine learning meticulously. In this article, you will get to know about the future role of the QA tester, when AI testing will take over.  Inaccuracies are greatly reduced in QA through the strategic application of AI: Both machines and humans have their pros and cons. Huge amounts of data can be greatly analyzed by machines, whereas humans excel in applying knowledge and exploring creativity. Humans a

  Agile methodology has become an important aspect of software development and testing activities and organizations are getting benefitted from it. Keeping in perspective the popularity and demand of agile methodology in the IT world, it becomes obvious for testers and developers to learn this concept from an implementation standpoint. In this article, you will get a brief idea about the basics of agile methodology in software testing. What is Agile? Agile is a set of principles that encourage communication, adaptability, flexibility and working software over processes and plans. Agile software development creates an environment where teams can collaborate and work efficiently on developing complex projects through constant communication and knowledge exchange. It consists of specific practices that focus on incremental and iterative techniques, which can be adopted and implemented in the software development process for optimal results. What is Agile methodology ? Continuous iteration