Comprehensive, testing fast-evolving systems rigorously, and covering the negative or unexpected scenarios that are most likely to cause a system to collapse.
Faster, with end-to-end automation of slow and manual tasks, not just the test execution phase.
Structured and measurable, using automated coverage algorithms to create the most rigorous set of tests possible, based on time and risk factors.
Simple and easy-to-use, with intuitive visual models and a range of accelerators, instead of complex scripting and keyword definition.
Plugged into your world, executing optimised tests using existing or homegrown frameworks, with connectivity into virtually any API, and support for Selenium, Appium, Testplant, and more.
Complete Test automation, Beyond just The Execution Phase
Test Modeller plugs into your existing test automation frameworks to eliminate the manual tasks that slow you down.
|End-to-End Test Automation with Test Modeller:
|Slow and Manual Automation of Test Execution:
1. Automation Goes Beyond Test Execution:
Generate test cases, automated tests, and data from easy-to-use visual models. A UI recorder, object capture, and requirements importers accelerate accurate modelling of the system under test.
1. Automating Test Execution Creates Slow and Manual Effort
Highly skilled automation engineers must write repetitious test scripts by hand, or configure intricate keyword-driven frameworks.
2. A Rigorous and Structured Approach to Test Automation:
Apply powerful mathematical coverage techniques to generate the optimal set of tests based on time and risk factors.
2. Wasteful Over-Testing and Low Test Coverage:
Automated tests are not measurable and repeatedly exercise the same system logic, leaving the majority of the system exposed to defects.
3. “Just in Time” Data for Every Possible Test:
Test data is found or created as automated tests are executed, using a comprehensive range of easy-to-use test data functions.
3. Low-Variety Test Data Undermines Testing Rigour:
Copies of production data can only execute a fraction of the tests needed for rigorous testing. Data is slowly moved to test environments, with new or unexpected scenarios created by hand.
4. Reactive Automation Keeps Up With Change:
Automated test maintenance is as simple as updating the visual model and generating up-to-date test cases, data, and automated tests.
4. ‘Automated’ Testing Quickly Falls Behind Changing Requirements:
Testers manually check and update existing tests every time the system changes. No time is left for testing new functionality within an iteration, and testing quickly lags behind the rate of change.