Manual and Automation testing for Schoolio

Schoolio is an online elementary education platform that offers access to popular courses for every grade through our marketplace. In addition, users can create their courses, lessons, quizzes, and review assignments.

The product was released to the market without a testing process. The project manager conducted smoke testing and developers – unit and integration testing.

Our specialist was responsible for developing regression test cases for the platform and their automation on the project. During the execution of these tasks, several nuances emerged that we would like to share.

To automate testing, TypeScript was used in combination with the WebdriverIO framework. The organization of the automation framework used the Page Object Model approach, which allows you to effectively structure and organize test code to facilitate the management and support of test scenarios. 

Regression testing was performed using Google Sheets for documenting test cases. Smoke testing was performed manually, without the use of additional tools. 

On the project, thanks to GitHub Actions, the interaction between the tester and the developers was improved by automating the testing and integrating with other tools. This made it possible to quickly identify and solve problems, ensuring high product quality and an efficient development process. 

The project required testing various user tests and quizzes, which created complexity in automation. For effective testing, a special file was developed that allowed testing of complex processes (for example, such user actions during testing as drag and drop actions, drawing lines between objects, multiple choice answers, and writing complete answers). Each test has been carefully selected, followed by positive and negative scenarios, and the results have been verified to ensure the high quality and reliability of the product. 

• 200 bug reports were created (using Jira), showing our great attention to detail and ensuring the stability and reliability of the project. 
• 10-15 non-critical bugs were identified and fixed before release, including video issues, security issues, and course editing. This has had a positive effect on the quality of the product and the satisfaction of our customers. 
• Out of 200 test cases, 126 were automated, which positively affected the efficiency and repeatability of testing, allowing us to find problems faster and improve product quality.
• Conducted usability testing: which helped to evaluate the ease of use of the product by users, identify problems in the interface, and ensure improvement of the convenience and efficiency of its use.