EnglishHelper Case Study - eLearning
EnglishHelper strengthens the literacy foundation of students from a young age, using an AI technology intervention. Have deployed reading and comprehension AI platform across thousands of schools globally
Time to coverage
2 weeks
to high-coverage regression suite
Automated tests delivered
100+
tests per app
Sprint-based,
multi-platform testing
Reduced QA cost &
Improved
cross-device coverage
Problem
- EnglishHelper has two web apps, one had partial automation with Selenium and the other one had no test automation
- Complete automation for both the apps was needed
- Maintaining Selenium scripts was cumbersome and costly
- Testing with multiple form factors, browsers and platform was a major requirement
Intervention
- Implemented automation with 100+ test cases for each app in just 2 weeks
- Tested apps on mobile, tablet and desktop with multiple resolutions
- Provided multiple APIs for test generation for new releases and test execution on multiple browsers & platforms
Measurable Outcomes
- For each new release of Apps, QASolve maintains the tests including adding new ones as needed
- QASolve’s Success team is part of the EnglishHelper’s sprint planning meeting to trigger new discovery and test generation
EnglishHelper Auto-Discovery
Auto-discovery involves systematically navigating through the application across all user journeys, identifying individual elements such as buttons, forms, links, menus, and other interactive components. Additionally, it captures how users interact with these elements, including sequences of actions, page transitions, and the overall flow of user interactions.
KNOWLEDGE GRAPH OF DISCOVERY
25 Pages
2703 Components
4926 Elements
8825 Events
“QASolve agents rapidly validate our SaaS apps on multiple browsers and devices. This has helped in reducing QA time as well as cost”
Deepak Verma
CEO