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AI-augmented, software-testing tools provide capabilities for advanced, self-optimizing and adaptive automated testing through the use of AI technologies, such as machine learning (ML), self-healing heuristics or computer vision. They assist humans in their testing efforts and reduce the need for human intervention in the following areas: Test case and test data generation Test suite optimization and coverage detection Test efficacy and robustness Test analysis and defect prediction Test effort estimation and decision making AI-augmented testing tools streamline, accelerate and improve the test workflow, as models can be retrained based on the data collected from the activities they perform — thereby enhancing human productivity.

• Opkey
  4.4

  11 Reviews

Mobile testing services are different from traditional application testing with additional complexity, such as the testing of multiplatform, networks, multiple operating systems (OSs) as well as different devices. These services are needed to test the function, performance, compatibility and other details of a mobile application, using both manual and automated tests. While the testing this market refers to is that of applications residing on mobile handheld devices, the testing must also take into account the data being gathered or supplied to embedded devices and sensors with the Internet of Things (IoT) becoming more prominent. User experience is key in mobility by creating unique requirements for the testing process. With digital business and customer experience, applications and data are increasingly available and visible to external constituents — especially customers. Thus, quality, reliability, security, and adaptability needed for external use of systems are far beyond internal usage.

• pCloudy
  4.8

  9 Reviews