A Revolution in Code Coverage
NCover 4 is a major leap forward in the ease and flexibility of code coverage tools. Code coverage, gathered while running unit tests against your code, shows the developer what code was exercised during the test and gives a specific measurement of unit test penetration. By tracking these statistics over time, you gain a concrete measurement of code quality during the development cycle.
The core of the NCover 4 application suite is a Windows Service which is installed with instances of Desktop and Collector. The NCover Service starts automatically and runs continuously in the background of your OS (Windows XP and higher), allowing NCover 4 to monitor .NET version 2.0 and higher applications and Silverlight 4.0 and higher.
When you're ready to improve your tests, the NCover Service is waiting to cover any type of code test from unit to functional to manual.
NCover 4 Code Central is an all-new browser-based application that provides a central hub for managing all NCover code coverage projects. Code Central also allows admins to create, edit and delete the accounts of users who are able to connect to the Code Central server.
Code Central allows you to configure projects and monitor coverage collection across a network of connected Desktops and Collectors. Code Central is not just a repository, it's an entirely new way of managing code coverage on a scale never seen before -- a truly distributed and interactive system of coverage collection and analysis.
Code Central helps you make sense of your coverage data by providing coverage metrics like Sequence, Branch and Method, and the high-level view of Change Risk Anti-Patterns, and Complexity. Metrics like the Change Risk Anti-Patterns (CRAP) score are a better measure of risk than coverage alone. Since it's extremely difficult to get to full coverage, CRAP score weighs the amount of uncovered code against the complexity of that code. Code that is more complex typically needs more complete coverage, because the more complex it is, the more likely it is to have errors. CRAP score finds methods that are least covered for a given level of complexity.