Organizations have tried to speed up and optimize software testing processes with continuous releases of high-quality software but with the evolution of Artificial Intelligence (AI) enabled solutions, testing has become more challenging due to the complexity involved in testing AI systems. According to a research report, it is expected that by 2025, the value of the AI market is said to surpass US $100B.
Specifically, AI- based systems testing is essentially difficult as different input and output combinations that are fed to the system should be tested which is more towards a non-deterministic approach. Moreover, as the world is increasingly moving towards increased adoption of AI-powered smart applications, there is every need for end-to-end AI systems testing to ensure fully functional and high-performing AI systems. Hence, in order to ensure effective AI testing, TestingXperts follows an effective, and comprehensive testing strategy for testing AI systems.
|A/B testing||• Classic AB Test, Split tests, and MVT to compare variations of features|
|API testing||• Understand API endpoints between UI, NLP, and data store|
|Non-functional testing||• Non-functional requirements like performance, security, usability, and accessibility|
|Input Data testing||• Different kinds of input values to test expected and unexpected behavior|
|UX testing||• Perform interoperability testing with multiple devices
• Perform user experience and accessibility testing
|ML testing||• Spoon-feed the AI with specific data to test the change in its behavior|
|Voice and NLP text testing||• Provide user input in the form of voice or text.
• Verify its capabilities to process intent and respond with the appropriate utterances