Test automation has become a key force in the software development ecosystem. Over 73% of testers use automated testing for functional and regression testing, while 24% have automated more than half of their entire testing process. But a gap exists between the development sprint and test automation within an agile framework. Agile methodology dictates that the development objectives should be divided into small chunks or sprints lasting as few as 15 days. While this approach has led to faster development, it has dented testing efforts due to a lack of time. Agile gives little time, if any, to testers to exhaustively test each piece of code and check whether they conform to the required business parameters.
It is within this scenario that in-sprint automation has found its relevance. With in-sprint testing, development and testing can run simultaneously, building better-quality applications without compromising delivery time.
In-sprint test automation is a process that leverages automation to conduct end-to-end testing of the AUT (application under test) within the same sprint it was developed in. Instead of the typical N-1 method used by most agile teams today, the QA team collaborates with the development team to test the same code. Since each functionality is developed and tested during the same sprint, there is no backlog for automation or testing. It necessitates efficient communication between all sprint participants, and it equally assigns the responsibility of the software testing process to each team member. In this collaborative effort, the sprint stories must be granular enough to be developed and tested within the sprint – developers write the code and conduct automated unit tests. At the same time, the QA specialists spend time building new automation scripts.
In-sprint automation contributes several vital benefits to the development process, making it tighter and more condensed with better quality returns.
Even though the advantages of in-sprint automation vastly outweigh the challenges, many development companies run into bottlenecks that impede their development pace. In-sprint automation challenges such as choosing the right test automation solution, building adequately granular user stories, accessing actual user conditions, poor collaboration and communication, and wrong dependency estimation can throw the entire cycle off track. Here are five best practices to tackle these challenges without losing precious workforce, resources, and time.
The QA team plays an integral role in agile development. Excluding them from crucial sprint meetings can leave them in the dark about essential product requirements and dependencies. This can become increasingly inefficient and force a lot of reworks. Moreover, the QA team can divulge critical information about test prioritization and testing time to help better plan the sprints.
Sequential test automation isn’t suitable for in-sprint testing. Instead, you need to adopt one of the following approaches:
In-sprint automation works best when complex dependencies are removed, and better modular flexibility is provided. To do so, testers require the successful abstraction of application components. Abstract components can use virtualization to set up their runtime environments and enable parallel testing.
Today’s software architecture rests on microservices and modularity. While this accelerates development, it can complicate testing due to several interdependent moving parts. Your automation capabilities must run deep into the tech stack and access each module and component to achieve successful in-sprint automation.
Your chosen testing solution can make or break your entire sprint cycle. It would be best to have a cloud-based, flexible, scalable, heterogeneous testing solution to run parallel tests across multiple browsers and platforms with little to no coding requirements.
To maximize the benefits of in-sprint test automation, you must pick a robust no-code testing solution like Avo Assure. Apart from possessing all the features mentioned above, it facilitates CI/CD integration with continuous testing. Its elastic execution grid and upgrade analyzer accelerate testing while intelligent reporting and intuitive UI/UX ensure a short learning curve for even non-tech personnel.
CNA Insurance, the US’s seventh largest property and casualty insurer, adopted agile development, optimized end-to-end testing, and improved test coverage with Avo Assure. They achieved in-sprint automation that reduced their testing cycles by 50%-60% and accelerated their time-to-market.
Book a demo with us today to enhance your testing speed and deliver products faster with in-sprint automation