Developing and delivering a popular software that will make people’s lives easier is not the challenge in today’s digitized world; there are many who can do that.
What makes an app or a software service stand out from the crowd is how fast it provides updates and whether those updates keep pace with customer aspirations and expectations. Just think about the fan expectations from the sequel of blockbuster movie or a book. An unsatisfactory update can be a killjoy for the original software, even if it was a game changer during its release.
This is what makes agile testing a go-to for enterprises which build software products that cater to the masses.
Agile testing is a philosophy which evangelizes collaboration between customers and testing teams to align development with customer needs at the center. The manifesto aims to hasten the process of software development whilst minimizing bugs. All this after planning for regular updates that will cater to the customer’s demands.
As opposed to the ‘Waterfall’ method, Agile brings in testing in the early part of the software development life cycle (SDLC). This effectively translates into testing more of the same, a tiresome and costly affair. Which makes Test Automation a necessity rather than a luxury.
Why agile automation testing?
A robust product designed for best customer experience
The biggest peeve of a user is the robustness of the software. A bad experience due to an unidentified bug can not only lead to higher bounce rate but also bad reviews which can be the death knell. In Agile Automation testing starts very early in the SDLC and hence, identification and fixing of glitches happens on the go, as opposed to when the complete product is ready. Bugs are not carried forward to the next stage of development which adds to the robustness of the software, while early identification also saves time, money, and effort.
Automation makes life easier for coders
Since the scripts for running automated tests can be reused, the repetitive nature of work is made easier by automation. An agile environment necessitates quick development. This requirement eliminates manual testing and thus also saves on effort that coders would have needed to put in. Running the same tests, multiple times also creates a solid database of issues which can help later during maintenance; in essence, automation also reduces maintenance costs. Enterprises can thus optimize the use of human resources and create more intricate tests that provide end-to-end testing of the product.
Seamless co-ordination between distributed teams
The agile methodology envisages constant flow of information between different teams so that the software can respond faster to change in customer requirements. With automated testing, defects and changes that need to be incorporated on the go, based on customer feedback, it becomes easier.
Higher precision leads to a more powerful product
The aim of automated agile testing is to reduce the number of errors and find them early. If the testing suites are designed properly at the start, the teams don’t need to worry too much later, as testing is automated. Artificial Intelligence embedded systems can also provide real-time data for review and incorporation of improvements earlier in the SLDC. For instance, Aspire’s Hyper-testing is an AI-led agile testing service which improves the testing team’s productivity, greatly leading to a more robust product.
Reduction of cost
All the above-mentioned features of agile automation testing ultimately help reduce overall costs and optimize human resources as well. In the traditional Waterfall method of testing, testing later in the day proves to be costlier affair; experts say the earlier a bug is detected and rectified, the less expensive it proves to be in the long run.
In conclusion, Agile automation testing ticks all boxes in case the software to be tested requires regular updates, is used by the masses, and has a number of features. The weight of expectations falls on the testing and development team, and inherent advantages of automation help lighten it considerably.
Aspire’s AI-led Test automation and AI-powered frameworks like AFTA and DCqaf support end-to-end testing with several added benefits.
How can AI improve the efficiency and accuracy of agile software testing?
AI can help improve the efficiency and accuracy of agile software testing in multiple ways. Following are some of the most popular ways in which AI helps agile software testing:
- AI helps with test automation: Automation is the most expected benefit of AI in agile software testing. AI at present is more than capable of doing that. With AI, you can reduce manual effort and human intervention. Making testing faster and budget friendly.
- AI helps with Parallel testing: AI can run tests across multiple environments, thereby reducing the time for testing. This capability not just ensures quick feedback potential but also helps accomplish your business to have quick releases of your software or products.
- AI helps with dynamic test case generation: AI keeps up with the continuous development of your applications. What it means is that it quickly identifies the code changes or new/unaccounted user behavior and creates relevant testing functions immediately.
- AI helps with Superior Test Prioritization: AI performs tests for the most critical part of your software first. This prioritization of choosing the most critical area is attained by analyzing risks involved and historical data. By empowering your business with superior test prioritization, you can better utilize your resources, especially for your larger programs.
- AI helps with Continuous Test Process Refinement: As the time passes, the testing requirements grow and change. The software of the future will demand a much more cerebral testing program than is available today. AI is equipped to solve this issue as well; it refines the testing as the changes happen making AI attached testing processes to be risk averse.
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