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Test Data Generation Principles

GEDIS Studio Online offers an innovative test data generation solution over the competition. Before diving into the online documentation of features and reference guide of generation rules we invite you to read about the basic principles of generating realistic test data with GEDIS Studio. 

Key Features

 The major features of GEDIS Studio can be grouped along the following topics:

  • design (create, reuse, share) your test data generators,
  • production automation of your test datasets,
  • preview generated data,
  • perform statistical analysis on the generated test datasets.

Design your test data generator

GEDIS has a graphical user interface similar to Eclipse IDE which is easy to handle (see demo). Without requiring knowledge of a developer or database administrator, the user can design a test data generator by putting together the generation rules provided with the tool.

There is more than 30 field generation rules you can use right away or combine with each other to define virtualy any kind of correlation or data constraints.

Produce test data samples

GEDIS Studio embeds a batch production service that saves you from much of the scripting work when it comes to produce multiple test data sets differing only on few parameter's values.

View test data files

GEDIS Studio offers many test data viewers depending on the selected output format. You can easily produce various file formats such as plain text CSV, XML, HTML, SQL or even generate programs and scripts.

Analyze test datasets

For more advanced checking you can take advantage of the GEDIS Studio analysis tool to control at a glance the demographic distribution of the generated data.

See also:

Data Correlation

test data correlationData correlation expresses the constraints between values of different fields in one or more records. To ensure the realism of generated test data, various types of constraints on one or multiple fields and records should be considered.

 

Data Distribution and Control

probability-distributionRandomly chosen data among reference values is fundamental to test data generation engines. But a pure random choice often neglects the representativeness issue. To reinforce the realism of generated data, the underlying engine should enable probability distribution to be controlled

 

 

Test Data Generator Features Overview

GEDIS Studio is a full featured application to support you in all the steps of your test data management. Below are an overview of the features, you can also dive into the application itself by wacthing the demos and tutorials.