The significance of software testing has intensified globally due to the Covid-19 pandemic as it forces us to shift most of our work dealings from home itself. We require software testing that quickly maximises business operations. In the past, software testing was restricted to find errors and offer product enhancement recommendations. Nowadays, the influence of technological advancement has changed the path followed for testing and quality assurance. The advantage of multiple tests across the SDLC (Software Development Life Cycle) shows the extensiveness of the process.
Transformation to QAOps
The specific meaning of QAOps is the integration of quality assurance (QA) and Continuous Integration channel. This model emphasises on integrating the process of software with the Continuous Integration pipeline. Based on this system, the QA team need to work with both development and operation teams closely. Under QAOps, DevOps is associated with continuous testing to assure any software developments are readily forwarded to the Continuous Integration pipeline’s production phase. It controls the problem of conducting software testing at uncertain intervals without any transparency on quality issues.
RPA Testing is Dominating the QA Process
The Robotic Process Automation (RPA) can also be called as an automation extension. We can apply RPA to anything that is in a structured form, unlike automation that needs a software product in order to work. RPA can be used in complicated processes that can be easily automated with AI. It is primarily an automation style wherein a machine mimics a human action and supports to complete rule-based tasks with developed robots. Therefore, this robot-led automation can transform the workplace and does all duties that are executed by the automation testing tools.
Performance Testing is Shifting to Performance Engineering
Product performance has been a significant segment of testing priorly, but now, it has been moving towards performance engineering, and it is not an easy process. The process of performance engineering involves the collaboration of software, hardware, performance, configuration, usability, security, and it assures to deliver the highest value that surpasses end-user expectations.
As per the latest report, Google says 53% of visits are left if a mobile site takes greater than 3 seconds to load. The rising demand for quick loading and high performing mobile and web apps require performance testing and performance engineering needed for all apps. Also, since the DevOps teams continuously deploy applications quickly, the applications’ performance engineering is in high demand.
Scriptless Test Automation
Test Automation has developed to promote rapid software releases at the top-notch quality. Automation has always been impressive, as it lessens the mundane testing exercises and expedites the testing process. To maximise the test automation scalability, ‘Scriptless Test Automation’ is launched. Scriptless test automation facilitates testers and business users to automate the cases of testing without the worry coding. It supports to achieve quicker results and lessens the time spent to understand the code.
Use of AI and ML in Software Testing
AI and ML have an even more significant impact on software testing. AI tools support QA teams to design tests from scratch with minimal or no human supervision. In specific, AI removes all unnecessary cases to speed up the process of testing. Based on the behaviour of the users, machine learning will help to predict the potential difficulties with more accuracy. Using AI and ML in software testing, we can enhance the accuracy of error identification and tracking.