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Challenges of the AI Testing Industry
Per Gartner, AI technologies will be in almost every new software product by 2020.
Whether it be the health, finance, or entertainment sector – every industry is trying to innovate and use AI-based apps that help automate tasks. This makes testing the apps for automation a business-critical activity. However, there are multiple testing related challenges that organizations may face while leveraging AI for testing apps for quality, such as:
- Identifying the exact use cases
- Lack of awareness as to what really needs to be done
- Verifying the behavior of the apps based on the data that has been input
- Testing the app for functionality, performance, scalability, stability, security, and much more for it to be successful
How Cigniti Leverages AI for Software Testing
In this era of daily deployments and DevOps transformation, organizations need to automate the test requirement traceability and versioning to accelerate the QA cycle and reduce overheads in test management and provide superior quality governance.
Cigniti’s Intelligent Test Case Management Strategy
- AI algorithms for:
- Test suite optimization
- Predicting the next for test suite queuing
- Log Analytics
- Defect analytics
- Integrated Requirements Traceability Matrix (RTM)
- Rapid impact analysis
- Comprehensive documentation
Assured Benefits of Cigniti’s Intelligent Test Case Management Strategy
- Faster deployments
- Matured governance over test data and test suite
- Better traceability with backward & forward integration
- Holistic approach with early feedback with unattended execution
- One integrated platform
Use our expertise in defect predictive analytics and test execution to ensure 100% coverage.