Data Design™ - dramatic test data design powered by test data creation

Datamaker Data Design™ - because there's no substitute for good test data.

Powerful test data design powered by test data creation; two key elements guaranting the effectiveness of testing

The painful truth is that too many test managers think that by using the HP/Mercury QTP solution they are covered in using correct and valuable test data.  They are only making an ineffective process just a bit more efficient. Turn your ordinary test and development data into Gold Standard data with Data Design™; Grid-Tools state-of-the-art, scientifically designed solution.

Grid-Tools Data Design™ is truly different from all of the "noise" in the marketplace today, as its primary focus is on ensuring you are using the right kind of test data.  Datamaker Data Design™ focuses on the following elements:

• Creating and generating quality test data for all testing and development projects
• Ensuring that the requirements are unambiguous, correct, complete and logically consistent
• Reducing the nearly infinite number of potential test to a manageable number
• Ensuring that the test produced the right answer for the right reason (i.e. it is the only approach that addresses propagating a defect to an observable point)

 

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Datamaker Data Design™ offers the ability to create rich combinations of data automatically, ensuring testing projects relying heavily on underlying data are much more effective. The 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 Design™ offers the choice of two test case design methods

Data Design™ 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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