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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.

• testRigor
  4.0

  2 Reviews

SOAPs enable I&O leaders to design and implement business services. These platforms combine workflow orchestration, workload automation and resource provisioning across an organization’s hybrid digital infrastructure. Increasingly, they are central to an organization’s ability to deploy workloads and to optimize deployments as a part of cost and availability initiatives. SOAPs provide a unified administration console and an orchestration engine to manage workloads and data pipelines and to enable event-driven application workflows. Most tools expose APIs enabling scheduling batch processes, monitoring task statuses and alerting users when new events are triggered and can be integrated into DevOps pipelines to increase delivery velocity. SOAPs expand the role of traditional workload automation by adapting to use cases that deliver and extend into data pipelines, cloud-native infrastructure and application architectures. These tools complement and integrate with DevOps toolchains to provide customer-focused agility and to cost savings, operational efficiency and process standardization.

• testRigor
  4.7

  4 Reviews