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5 Best Practices for Efficient Mobile App Testing

June 15th, 2020 by

With consumer base increasing demands for mobile applications, companies are committed to boosting the efficiency of mobile devices. To provide the best user experience, it is extremely important to include Mobile App Testing in the process for application development.

In a rapidly advancing mobile app development environment where we are concerned with Continuous Integration and Web DevOps, product engineering is often conducted during the development process, and it makes no sense to push the system testing until the end.

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Therefore, research must always be carried out regularly and in general at all stages of the creation of the device process. To leave no stones unturned, QA Teams often come up with creative strategies for optimizing the testing of smartphone devices. But we’ll reveal the five most important activities in this blog to improve the productivity of mobile device development in terms of both consistency and volume.

Implementing Agile Methodology

Agile methods are the most common among all the SDLCs due to their modular design and the fact that the production and monitoring department works very closely with the customer to achieve productivity with this model. And because of the constant reviews, the willingness that Agile offers the managers to collaborate with the companies improves the efficiency of the final product. However, one significant advantage of this approach is that it helps the teams to produce the digital product in pieces that can be weekly or monthly.

Adopting Mobile DevOps and Agile Methodology

To achieve quality speed, it’s no brainer that it can be achieved with the two fundamental principles Agile and DevOps. We have already discussed that Agile allows the teams to get closer to the business which ensures qualitative results are achieved.

DevOps aims you develop digital applications efficiently, as it allows you to build codes ready to launch. DevOps stands for Dev + Ops. DevOps can be very finely defined as a practice or methodology where you combine the development with the operating part of building a product into one iterative loop so that the next stage can be fed by each stage of development and operation.

Implementing a CI/CD Pipeline

A ci/cd pipeline is a production pipeline combined with automated monitoring tools and servers to allow for seamless integration and continuous development with the aid of regular feedback loops, enabling teams to execute smaller bits of updates in a shorter period. This is an apt pipeline interpretation of the ci/cd. Let’s break that definition and try to comprehend CI and CD.

CI -Unlike the conventional SDLC in Continuous Development, the project is updated several times and reviewed in very early stages and once the bugs are patched the design is moved on to the production server for delivery. Thus, small chunks of codes are tested in the early stage in continuous integration, enabling the ready to deploy code, thus increasing the speed of software development.

CD- Once the bugs are fixed ready to be deployed on the mock production server. In the same way, multiple releases of codes are deployed in continuous delivery as several commits are made in a day of continuous integration. Every chunk of code is developed, tested, and even supplied to the mock server in this way.

As a ci/cd pipeline is meant to deliver the smaller chunks of codes and deploy them on an hourly basis on a server, it is obvious that it increases software development speed by many folds. We can also see that the ci/cd pipeline is pretty systemic, and it’s important to incorporate a ci/cd pipeline to streamline the phase of device creation.

Implementing Continuous Testing

Continuous testing is the method of evaluating every level of the production cycle with an application. As seen in the image testing can be performed in all the DevOps phases. We can also see that from quite an early stage the study starts, unlike conventional testing. Continuous testing can be implemented from planning to deployment, not only where code is written, built, or developed.

 

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