Mobile test automation

Usually, Agile, DevOps, and TestDevOps methodologies allow you to deploy the QA process before development even begins. This is especially good for automation, which requires preparation and scripting in advance.

Scripting takes time and resources, but the efficiency of testing compensates this drawback. Code that is once written can be reused, for example, during regression testing. 

The speed of running tests also increases, especially if the cloud with emulation or physical connection of target devices is used to run them. This allows you to parallelize tests and run multiple software versions simultaneously rather than sequentially.

As a result, the speed of testing increases many times over when compared to the manual method. In addition, by eliminating the routine, experts can focus on other priority tasks, thereby increasing the quality of QA.

In today’s IT industry, the processes of developing and testing digital products are so closely linked that their synchronization qualitatively affects both operations simultaneously.

The benefit of automation is that all processes can be integrated into CI/CD tools, such as Jenkins, and effectively manage the work of all project participants. For example, when a bug is detected, a bug report is automatically or manually created, which is placed in the pipeline with a note of priority. This indicates to developers the problem that needs to be solved now or a little later. 

Due to such close integration, work flexibility is ensured when priority goals are solved at once, and critical problems are not lost and migrate from version to version. Accordingly, by closing these tasks at once, developers save time in the further process of creating a digital product. This has a positive effect both on the efficiency of the work and on the final release time of the application.

The more QA experts are involved in a project, the more difficult it is to manage this team, delegate tasks, and monitor the progress of the work. The key problem of manual testing is the need for many resources to ensure quality and cover all relevant tasks. 

On the other hand, automation has an advantage: about 90% of all tests can be transferred to the script algorithm and run when necessary. You do not need a large staff for this. Only 1-2 QA Engineers with development skills and knowledge of programming languages are enough. 

As a rule, up to 3 testers and 1 project manager are enough to solve the remaining 10% of tasks. This applies to small and medium-sized projects with a minimum number of features and integrations. For large-scale IT products, a team of more than 10 experts of different levels and specializations is involved.

Let’s describe the procedure using the work of Zapple Tech experts as an example. 

First of all, we get acquainted with the specifications of the future IT product, its technical stack, functionality, and architecture. This allows us to prepare in advance directly for testing, assemble the team, write cases, and prepare tools and test environments, both locally and in the cloud. 

We then allocate experts from the Zapple Tech staff who will participate in the project. We select staff so that their experience and skills are relevant to the technology stack and the specifics of the digital solution. QA Engineers also proceed to create scripts and scenarios to automate testing. 

After the start of development, we also start testing, trying to detect errors in time and delegate the task of fixing them to coders. 

Upon completion of the development process, we compile and optimize the digital solution’s technical documentation, characteristics, and specializations and hand them over to the customer. We provide periodic verification of the IT product at the customer’s request.

As a rule, specialists encounter the following problems during the classic manual test:

• high expenditure of resources;
• complex team management;
• inconsistency of testing and development processes;
• incomplete coverage of test tasks;
• long testing process.

Automation contributes to their solution by:

• a relatively small team of specialists;
• the use of CI/CD tools;
• synchronization of the roadmap;
• use of cloud testing environments;
• code reuse.

Involving QA Engineers in the process increases the speed of developing automated scripts. They, in turn, increase the speed of tests and allow tests to be parallelized in an isolated environment, improving coverage of target devices, operating systems, or browsers.

Taken together, automation reduces the resource cost of conducting all test processes while increasing their efficiency. The scripts achieve almost 100% coverage of test tasks and reduce the time required to perform a full comprehensive QA during digital product development.

The final cost of a digital solution testing project can reach impressive amounts of hundreds of thousands of dollars. But the figure depends entirely on a number of factors that directly or indirectly affect the speed, complexity, quality of QA, and, of course, the pricing model. 

Suppose we’re talking about a small or medium-sized project with a limited number of features and a popular technical stack. In that case, the cost of its full verification will be relatively small. It will take no more than 5 specialists and a few tools, usually with a commercial license. 

Things are different with large-scale projects such as AAA video games, corporate systems, or other digital products. Their testing requires a large team, a whole arsenal of tools, frameworks, and software systems, and a very high level of skills of QA specialists. Accordingly, the price of such projects will be many times higher than, for example, a marketplace or mobile application with a budget of $100,000.