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<< Double Hump Normal Distribution | User Abandonment >>
<< Double Hump Normal Distribution | User Abandonment >>

Determining Individual User Data

Figure 13.6 Double Hump Normal Distribution
To implement this pattern, simply write a snippet of code to generate a number between 1 and
100 to represent a percentage of users. If that number is below a certain threshold (in the graph
above, below 61), call the normal distribution function with the parameters to generate delays
with the first distribution pattern. If that number is at or above that threshold, call the normal
distribution function with the correct parameters to generate the second distribution pattern.
Determining Individual User Data
Once you have a list of key scenarios, you will need to determine how individual users actually
accomplish the tasks or activities related to those scenarios, and the user-specific data associated
with a user accomplishing that task or activity.

Unfortunately, navigation paths alone do not provide all of the information required to
implement a workload simulation. To fully implement the workload model, you need several
more pieces of information. This information includes:
How long users may spend on a page?
What data may need to be entered on each page?
What conditions may cause a user to change navigation paths?
Consider the following key points when identifying unique data for navigation paths and/or
simulated users:
Performance tests frequently consume large amounts of test data. Ensure that you have
enough data to conduct an effective test.
Using the same data repeatedly will frequently lead to invalid performance test results.