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Modeling in Test Case Designer

Both approaches described below are viable, and the choice will depend on the specific system & testing goals, as discussed in the “Decision Points” section later.

Approach 1 – Whole response profile per test case

This is similar to the model designed in the API article. We will have a TCD parameter for each eligible request and response attribute that a) varies in finite manner; b) needs to be validated.

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Side note: if there are attributes that don’t have format variations, can’t be blank and therefore wouldn’t become TCD parameters, the steps & validations for those would be hardcoded (i.e. without <> syntax) in the script.

Approach 2 – Attribute per test case

To enable this in TCD, we will “transpose” our thinking from Approach 1. We will have a pair of parameters – “Validation Element” (the list of all non-status response attributes we need to check) and “Validation Value” (the list of all non-status response values we need to check).

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A single script with a single “Then” line would cover all scenarios, because the key wording is dynamically tied to the TC table:



Decision points

Approach 1 – Pros:

  • If there is any validation dependency between response attributes, this approach has a much higher change to catch defects.
  • Less vulnerable to setup costs per TC (i.e., in an absurd example, if each test requires a unique API token that costs $1000, then executing a test per response profile is much cheaper than a test per attribute).

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Side note: “number of tests” as a metric becomes irrelevant in this comparison since the number of steps per test and the corresponding execution time/effort are too different.

Conclusion

Hopefully this article has demonstrated how Test Case Designer can be applied to use cases where n-way interactions are not really the priority anymore. The speed of scenario generation and the one-to-many scripting move into the spotlight, so the tool can still deliver benefits in either approach.

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