## The Use Case

Suppose you have some rules that operate on a data payload that can have many possible combinations of data values. During testing how can you be sure that you have covered all the possibilities? Including all the possible ways the data can be bad? Running your test against production data probably won’t help. Even though you may have millions of records, chances are you won’t find every possible combination of the data.

So is there a way that Corticon could help to generate test data?

Yes, Of Course!

Let’s imagine we have some business rules that evaluate meals at a restaurant.

A meal consists of a starter, an entrée, two sides, dessert and coffee

For example here are some possible meals

Starter is Soup or Salad

Entrée is Chicken or Beef

Sides are Fries, Peas, Carrots, Broccoli

Dessert is Ice Cream or Soufflé

Coffee is Regular or Decaf

Here are a few possible meals

soup, chicken, broccoli, fries, ice cream, decaf |
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salad, chicken, broccoli, fries, ice cream, regular |
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soup, chicken, carrots, fries, no dessert, regular |
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soup, chicken, broccoli, fries, ice cream, regular |
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salad, beef, broccoli, fries, ice cream, decaf |
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soup, chicken, broccoli, carrots, soufflé, decaf |

If we also know the price (or calories) of each of the meal components we can compute the total cost (calories) of each meal.

Perhaps we want to determine which meal is cheapest or has least calories