Generate test data to enhance the quality of your tests – watch a demo

Are you tired of coming up with endless amounts of test data to improve the coverage of your tests? We’ve got good news for you.

Our November update brought to you the highly anticipated test data generation feature to code coverage analysis tool Coco — Say Hello to Coco Test Engine! 

Coco Test Engine in action 

In the video below we’ll give you a comprehensive look into how Coco Test Engine works to help you reach higher code coverage faster. 

What is Coco Test Engine? 

Coco Test Engine is a test data generation feature from the Coco 7.0.0 release that will take your testing process to the next level. It’s designed to:

• Help you reach the highest feasible coverage level faster
• Sort out redundancies in code coverage analysis
• Provide automatic collections of test data that includes edge cases 

Why you’ll love Coco Test Engine? 

Coco Test Engine automatically generates test data to improve the quality of your testing and helps cover various edge or error cases that human testers could have easily missed. 

All you need to do is put the algorithm to work and let it find cases that you don’t normally cover, or complete the existing test suite. 

In the past, software developers were also responsible for the tedious tasks of coming up with their own unit tests and test data. 

Considering that the testing code base needs to be larger than the production code in order to achieve a very high code coverage, manual test data generation does not cover all potential edge cases you should test for. 

Additionally, when the code becomes too complex, the possible combinations of input parameters and the test cases grow exponentially too. It makes the final stretch of code coverage very time-consuming and difficult to achieve. 

This is where Coco Test Engine enters the picture to get you through that final stretch. 

How does Coco Test Engine work its magic?

Coco’s test data generation reduces the complexity of writing data-driven tests in three ways:

1. It separates test code and test data. For many test frameworks, the concept of data-driven testing is not provided, which means that the developer needs to write a separate function per test data. If supported, test data generation and the unit test code are put on the same file, which imposes that the data conforms to the C++ syntax and increases the size of the unit test code.
2. The data editor makes it easy to review and edit tests in spreadsheet form.
3. The set of tools helps discover new test cases but also streamlines the processes of updating test data with code changes, and data validation by the tester.

Learn how to set up Coco Test Engine and increase your code coverage

Try it yourself 

Experience faster and more complete code coverage analysis. Start a free trial with Coco →

Or find out more about our code coverage analysis tool →