As the software keeps growing, the testing process also becomes quite challenging. Winning and losing the business depends on the quality and time taken to deliver what the customer needs. Many organisation’s adopted agile and Devops methodologies to embrace variation whereas the traditional testing process still remains slack and not able to act in accordance with changes. To address these complexities and challenges, Quality Engineering experts have come up with Hyper-Testing.
Hyper-Testing: All Inclusive
Hyper testing is an agile approach towards executing a full-cycle test strategy that combines a set of advanced tools and techniques to enable testing at digital speed and scale within shorter timelines while optimizing cost and efforts.
In simple terms, the focus is to design and execute a full-cycle test strategy that covers end-to-end testing of all application layers as well as the non-functional requirements and automates QA process to ensure maximum test coverage and quality resulting in lower TCO and higher ROI.
AFTA (Aspire’s Framework for Test Automation) is a powerful framework to employ Hyper-Testing. This powerful automation framework integrated with the continuous testing tools to really power the continuous testing process.
What Hyper-Testing Offers?
Hyper-Testing incorporates 3 key aspects that addresses a host of processes, practices, tools and reusable assets to drive agile testing at greater speed and cost efficiency. The following are the various dimensions of automated testing comprising all aspects of enhancing development:
- Incorporating a solid set of Testing Frameworks and vital tools integrating Cloud based Automation and Continuous Testing to sustain the end-to-end product- development- cycle.
- Augmenting testing in every phase of the application and technology stack, to ensure bug-free and uninterrupted performance of the product across various domains and platforms
- Deploying numerous process methodologies to enhance the digital customer such as
- Verify requirements
- Validate functional and non-functional end-to-end testing requirements
- Validate end-to-end system integration testing
Hyper-Testing automation using AI
The impacts of implementing AI with test automation results are:
- Self-healing scripts to identify changes in the application
- Analysis of the test automation results
- Defect Analytics on the severity of the bugs
- Auto Update of defects in defect tracking tool
- Build Analytics on the previous runs
- Live Streaming of the test results with Intelligence