Keysight Eggplant Features

Tests software, websites, and servers by applying stress on all components

Pushes extreme situations to test high-use or high-impact components

Offers test variety from user experience to backend performance, and more

Generates reports regarding load testing successes, failures, and concerns

Provides developers with actionable insight after running tests.

Maintains a thorough history of test logs for future reference and analysis.

Grants developers granular control to define tests and test parameters.

Allows developers to automate a wide variety of test types according to need.

Automatically assigns relevant followup tasks and notifies appropriate team members of status after testing.

Runs tests automatically and reliably according to the parameters and frequency defined.

Tests completely and thoroughly to minimize developer workload.

Supports integration with multiple data sources for seamless data input.

Enhances output accuracy and speed through efficient ingestion and processing of training data.

Generates actionable insights by applying learned patterns to key issues.

Continuously improves and adapts to new data using specified algorithms.

Capability to perform complex tasks without constant human input

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Capability to perform complex tasks without constant human input

Engages in human-like conversation for task delegation

Anticipates needs and offers suggestions without prompting

Effectively creates tests by recording or analyzing user interface interactions.

Accurately translates plain-language descriptions into functional tests.

Provides AI-driven recommendations for improving test coverage.

Tests effectively self-heal to adapt to changes in the application.

Identifies application elements even after their properties change.

Reduces the time and effort required to maintain existing test suites via AI.

Provides insightful dashboards and reports for understanding test results and overall application quality.

AI accurately identifies unintended visual changes or bugs in the user interface.

Analysis clearly pinpoints the root cause of test failures.