Gartner defines AI-augmented software testing tools as tools that provide fully integrated and orchestrated capabilities to enable continuous, self-optimizing and highly autonomous testing in the software development life cycle (SDLC) through the use of AI. Capabilities include the generation and maintenance of test scenarios, test cases, test automation, test suite optimization, test prioritization, test analysis, and test value scoring. As part of the larger toolset for AI-augmented development that aids software engineers in designing, coding and testing applications, AI-augmented software testing tools integrate with AI code assistants, chat interfaces, DevOps platforms, planning and deployment tools. They are delivered primarily as cloud-hosted services with some options for on-premises deployment. AI-augmented software testing tools are designed to simplify and accelerate the creation, maintenance and management of test artifacts throughout the SDLC. They help software engineering teams to increase the efficiency, effectiveness and fidelity of tests by reducing human intervention. Teams can build confidence in the quality of their release candidates and support software engineering leaders in making informed decisions regarding product releases.
Gartner defines adversarial exposure validation (AEV) as technologies that deliver consistent, continuous and automated evidence of the feasibility of an attack. These technologies confirm how potential attack techniques would successfully exploit an organization and circumvent prevention and detection security controls. They achieve this by performing attack scenarios and modeling or measuring the outcome to prove the existence and exploitability of exposures. AEV is generally delivered as a SaaS solution with or without on-premises agents. AEV technologies provide automated execution of both simplified and/or extensible attack scenarios. Results data from an executed attack scenario is used for various outcomes, such as: validating a theoretical exposure as real, automating frequent controls testing, improving preventive security posture or improving detection and response capabilities.
IT Security refers to products and services that protect digital systems and data from cyber threats and unauthorized access. This category includes markets that focus on network security, identity management, data protection, and cloud security, enabling organizations to reduce risk, ensure compliance, and operate securely in a digital world.
Load Testing Tools determine the performance of a system, software product, or software application under real-life based load conditions and resource utilization levels. The goal of load testing is to improve performance bottlenecks and to ensure stability and smooth functioning of software application before deployment. Through specialized testing software,various scenarios are simulated to test the system’s behavior under different load conditions. The software places a simulated “load” or demand from multiple sources on applications to ensure it remains stable during operation and peak load. It enables test analysts to evaluate application performance and maximize the operating capacity of the application.