Focus on test areas that are affected and essential. Automate only what really makes sense. Don‘t waste time with double or ineffective testing.
Maximize software quality
Have a clear picture which business risks are covered with your Test Cases. Give the best feedback to developers in order to minimize defects. Test early and often to save resources.
Speed up release cycles
Know exactly where an automation gains maximum benefits. Get transparency about challenges early in the development process. Achieve a high test coverage with less test cases.
Calculate the perfect test execution plan at any point in time
iTest keeps track of a wide range of attributes of each test case. Based on this test case DNA, iTest dynamically calculates the perfect test execution plan taking into account the available testing capacity. This ensures that the right things are tested at the right time and using the maximum available resources.
Focus on the most critical tests from a business risk perspective
iTest collects data from production monitoring systems, test tools, source code management software, service desk incidents and other solutions. It then uses machine learning algorithms to automatically calculate the business risk coverage of each test case, which allows to focus on highly critical test cases and to ensure a minimum number of production issues after each deployment.
Stop wasting resources on obsolete test cases due to over-automation
Test cases that are rarely executed and that require a lot of maintenance should be run manually. iTest identifies test cases for which automation adds value by taking into account specific attributes of the test case DNA, such as frequency, complexity, stability and risk.
Avoid testing the same code multiple times
iTest links test cases with source code, which allows to significantly reduce the number of test cases while maintaining the same level of quality. Test repository maintenance is reduced to a minimum and test case execution speed increases.
Foresee potential side effects after code changes
iTest tracks changes on a source code level and uses artificial intelligence to highlight potential side effects triggered by code changes.