Quality is the keyword for gaining customer satisfaction and approval, and it is the main ingredient that has been mulled over again and again by experts in the Software Development Industry. To gain top-notch quality and ROI, organizations need to upgrade their Quality Assurance practices to a whole new path in this age of agility and aggression in terms of market expectations, such as implementing complete test Automation in an end-to-end testing scenario based on a DevOps platform.
Agility in delivering the product in a rapid manner and providing the same amount of after-support is necessary for gaining market value for your brand. Organizations are always eager to stay on top of the competition when it comes to innovation and Continuous Delivery. Hence, the idea of eradicating the existing challenges faced by QA by way of upgrading the methods into a complete package that provides faster market-time is kindled.
In the era where AI ( Artificial Intelligence) and Data science plays a major role in capturing people’s minds and delivering faster results in a nanosecond, organizations, as well as customers, expect their software to be updated frequently, and for everything to be available in the market right away! To achieve continuous delivery and to exceed expectations, development and testing methods cannot be flawed and slow-paced. Hence, the solution for software product owners is to include newer methods and trends in their QA and Development phases and be updated in the industry.
How is traditional Quality Assurance a bottleneck?
‘Speed’ has always been a bottleneck in the Software testing scenario, and the QA teams have been integrated with the Agile and DevOps methods to intensify the test approaches and implement Continuous Integration/ Continuous Testing/ Continuous Delivery, but still, as per The World Quality Report, 2017 – 2018 released by Capgemini, adoption of QA with DevOps in an Agile environment is still slower among many companies. It says that only 45% have fully adapted their QA to Agile and DevOps methods, and almost 20% are still underway in grasping the methodology in their process, while the remaining 35% have not yet considered changing their old methodologies yet.
As the traditional QA methods aren’t adoptable to end-to-end testing cycles and in coordinating with all the other stakeholders, which helps in eliminating root causes of errors right from an early stage, there tends to be shortcomings with adaptability to the latest trends and delivering according to the current market speed.
Challenges Faced by Quality Assurance practices!
Preparing test cases for automation in advance and reusing the functional test data can be of more use to streamline the QA process than just using different testing techniques over various end phases after product development. Quality Assurance is a quality process that was not given the required attention that it needs for a long time until recently over the last few years, but then, Quality checking has become an integral part of the entire product development cycle to better the chances of faster time-to-market and higher ROI!
Some of the main challenges faced by QA professionals that need to be rectified with faster and more effective methodologies are;
Test Automation– Testing from one stage to another with manual effort will employ a lot of time and resources, which becomes a hardship for the delivery pipeline to stay in the market delivery performance level! Automation testing uses fewer amounts of resources, pre-planned cases, and proper scripts to reduce time, cost, and effort. Automating the entire Quality is still impossible, but it has become a goal for Organizations to automate at least more than 50% of the entire process, to reduce manual involvement to a minimum which reduces human errors and time consumption.
Scalable Testing- Scalability is a well-known issue, with the unfathomable amount of collected data involved in the world to consider. With Billions of people using every single application and software available in the market, the amount of coding and programming for every scenario and the number of algorithms involved are humongous, based on the inputs which are gathered often. Scaling the product to go up is a huge challenge as the expectation to handle larger amounts of data is not met by most of the software. Automating most of the testing requirements and rigorous testing with frequent recycling of cases is much needed to tone the process to meet the level of coding that can handle this huge amount of data. This is hugely based on the trial- and error method and can be adopted by turning Quality Assurance into Quality Engineering, which is designed to test for hundreds of scenarios.
Time- To- Market – The time-to-market is the deciding fate of a product, like continuous delivery and the need to produce the product in the market in a shorter period of time with support after the product has been released with lesser turnaround time, is a performance factor. To increase the product release and turnaround speed and to improve error detection before production, end-to-end testing cycles with Complete Automation boosted by Frameworks have to be in place. End-to-end testing methods such as Quality Engineering uses tools like Selenium and cloud testing integrated with other stakeholders in a product development cycle to complete time-consuming testing phases in a shorter period of time, by testing early and testing often!
Skilled – Resources – Finding the right kind of testers to integrate with other stakeholders, perform course codes, and have more knowledge of programming hasn’t been a necessity in the older QA methods! The traditional QA professionals had the mandatory domain knowledge and took care of testing on a need basis by concentrating mainly on testing the product towards the end of the product development cycle. Quality Engineering uses skilled testers that have extensive knowledge of performing test cases for Automation, coding, and programming when reverting to developers can take excess time, and integration with stakeholders from design until production and providing ample support after the products are being used by Customers, which is more advantageous than the traditional QA!
How is Quality Engineering a Better choice?
Quality Engineering is an end-to-end testing method that makes use of Frameworks, Cloud testing, and Selenium testing to provide faster and accurate results. It conducts rigorous testing and performs Quality checks as and when needed even during development by working along with the respective stakeholders!
Making perfect uses of cloud testing platforms and conducting multi-browser, cross- platforms, device testing has never been easier with the immense amount of methods and tools available when it comes to Quality Engineering. Frameworks like AFTA (Aspire’s Framework for Test Automation) and DCqaf (Digital Commerce Quality Automation Framework) consist of tools and platforms for performing testing of all kinds and make Complete Test Automation achievable.
When Quality and Agility become a main concern in the industry, it is better to deliver a product as per expectations without escaped bugs and in a shorter time. The performance of the product after its release into the market is solely based on the amount of performance testing and scalability testing it has gone through, and QE takes it to the expected level by performing continuous end-to-end testing profusely. The concept of Quality Engineering and in-depth analysis of the challenges faced by QA and its many solutions are covered in Aspire’s ebook.
- Automate Testing by at least 50 percent
- Scalable Testing
- Finding skilled resources
- Adoption of Agile and DevOps methods still slow in companies
- Difficulties in grasping the technology
- Inertia to adopt the new technology
- Helps deliver a product as per expectation
- Lesser bugs
- Faster time-to-market
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