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Grid-Tools Powerful Test Data Generation and Test Data Design

The Grid-Tools/Bender RBT Test Data Design Tool offers the ability to create rich combinations of data automatically, ensuring testing projects relying heavily on underlying data are much more effective.

The combination of the Bender RBT Test Case Design and Requirements Based Testing tool and the Grid-Tools Datamaker synthetic test data generation tool offers a realistic method to create fantastically rich sets of test data that would have been impossible using manual techniques.

The two respective technologies improve the effectiveness and efficiency in key areas of testing and test automation including; ensuring better code coverage, the detection of numerous defects and bugs and the management, manipulation and creation of test data.

Most data used for testing:

• Is entered manually into a test system
• Is entered using a test automation tool such as QTP
• Is a direct copy of a production database

Each of these methods is flawed, as none of them provide the rich combinations needed for high quality testing.

        

Data Coverage offers the choice of two test case design methods

The Grid-Tools/Bender RBT test data design component comes with two distinct test case design engines. When you invoke this directly you will be given a choice of which you would like to use.

Cause-Effect Graphing (C-E Graphing) takes you to the Graphing based test engine. Quick Design (QD) takes you to the Pairs-Wise based test engines. This includes Orthogonal Pairs and Optimized Pairs. C-E Graphing is intended for business critical, mission critical, and/or safety critical functions. It ensures that you not only got the right answer, but that you got the right answer for the right reason. It addresses the fact that multiple defects can sometimes cancel each other out. C-E Graphing ensures that defects are propagated to an observable point where testers can see the problem. QD is aimed at testing user interfaces (e.g., web pages, screens in client server applications. It is also applicable in designing configuration tests and quick shake-downs of even critical functions. Both C-E Graphing and QD address reducing the nearly infinite number of potential tests down to small, highly optimize test libraries. They both have full constraint rules support (One and Only One, Exclusive, Inclusive, Requires, and Masks) to ensure that the tests created are physically possible while still supporting full negative testing.

      

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