Industry: Healthcare
Platform: Web, IOS
Country: USA
Implementation time: Mar 2024 – present
Services provided:
Manual Testing, Functional Testing, Regression Testing, Exploratory Testing, API Testing, Integration Testing, Smoke Testing, Cross-Platform Testing, UI/UX Testing, Accessibility Testing
The project is a medical platform designed to analyze brain activity data and generate reports on the condition of patients. The application integrates with specialized devices for reading brain waves, providing doctors with accurate data for diagnosis and treatment. The platform includes a web version and an iOS application, which required a flexible approach to testing.
Before the introduction of a full-fledged QA process, testing in the project was performed by one tester, who was engaged exclusively in manual checks. The main focus was on functional, regression and smoke testing.
Test documentation existed only partially and covered only the functionality that had already been developed, which made it difficult to control quality when adding new features. At the same time, design documentation was available and described the key principles of the system. Test automation was absent at that time, but its implementation was planned for the future. The bug-fixing process was unstructured, which made it difficult to track and fix defects.
✅ The number of bugs before release has decreased by 4-5 times, the product goes into production with a minimum number of errors, reducing the risk of failures and improving the user experience.
✅ 400+ test cases have been created, covering functional, regression and exploratory testing, the coverage of key scenarios has increased, which helps prevent unexpected failures.
✅ 226 bugs have been recorded and fixed before going into production, which reduces the cost of fixing errors after the release.
✅ Test automation has been started, a framework, reporting and CI/CD processes have been configured via GitLab, which speeds up the testing process, which automatically checks critical scenarios with each update, reducing the need for manual checks and accelerating the release of new versions.
✅ The percentage of automated testing continues to grow, which over time will minimize the costs of manual testing, which in the long term reduces testing costs and increases the efficiency of QA processes.
Test Squad provided one QA automation engineer. The client’s main request was to ensure high-quality testing of web and iOS applications, identify defects at the early stages of development, and automate testing in the future.
| Completed work | Result |
| Developed detailed test cases covering functional and regression testing. | Complete testing of all key functionalities is guaranteed and the probability of failures is reduced. |
| Introduced a test case management process to systematize testing and improve efficiency. | Systematized work of testers is ensured, which accelerates the testing process. |
| Prepared documentation and identified key scenarios for future automation. | A basis for implementing automation is created, and costs for preparing tests in the future are reduced. |
| Developed a cross-platform testing strategy for uniform standards in web and mobile versions. | The stability of the application on different platforms and devices is ensured. |
| Introduced detailed testing reports, including PDF reports with test analysis, detected defects, and recommendations. | Transparency of testing is increased, and analytics and identification of problem areas are improved. |
| Included priority bug lists, highlighting blocking and critical defects. | Developers promptly receive information about critical defects, error correction is accelerated. |
| Generated Zephyr reports with detailed analytics of test execution and defect tracking. | A deep understanding of the current state of testing and defects is ensured. |
| Formalized the QA process, testing became systematic, errors are recorded and fixed faster. | The QA process has become manageable, testing is faster and better. |
| Conducted manual API testing using Postman and Swagger to check endpoints and documentation. | The correctness of API integrations is guaranteed, the risk of errors in interaction with the server is reduced. |
| Configured Postman Flows to automate repetitive API testing scenarios. | Automation of repetitive scenarios has made it possible to speed up API testing, reduce the load on testers. |
| Introduced a process for early detection and elimination of critical defects before releases. | The number of bugs in production is reduced, the quality of released releases is improved. |
| Developed a reporting system, including: – Daily testing reports. – Final reports on regression testing before each release. – Defect reports with full descriptions and priorities. | Transparency and control of testing are ensured, which accelerates the identification and correction of errors. |
| Conducted cross-platform testing (Web & iOS) to ensure stability. | Improved stability on different devices, reduced risks of platform-dependent defects. |
| Optimized team collaboration through a clear reporting system, which allowed developers to more effectively prioritize defect fixes. | Optimized the error correction process, developers received clear priorities for fixing bugs. |
| A basis for automation was formed – key scenarios subject to automated testing were identified. | Laid the foundation for further automation, which will reduce testing time in the future. |
Manual Testing: Zephyr, Postman, Swagger, Jira
Automated Testing: Webdriver.io, VS Code, Allure report, Appium, GitHub, BrowserStack