Codermetrics

Name

Power

Synopsis

Purpose

Measure the average complexity of the tasks that a coder completes.

Formula

Power = Points / Utility

Example

Coder A completes the following tasks in two development iterations:

Iteration 1: Task 1 with Complexity 3

Iteration 1: Task 2 with Complexity 2

Iteration 1: Task 3 with Complexity 4

Iteration 2: Task 4 with Complexity 1

Iteration 2: Task 5 with Complexity 4

Iteration 2: Task 6 with Complexity 2

Iteration 2: Task 7 with Complexity 1

First obtain the coder’s Total Points as the sum of Complexity for all completed tasks:

Total Points = (3 + 2 + 4 + 1 + 4 + 2 + 1) = 17

To obtain the coder’s Power Rating, divide the Total Points by the number of tasks:

Total Power = 17 / 7 = 2.43

You can also examine the Power rating within individual iterations and across iterations:

Power Iteration 1 = (3 + 2 + 4) / 3 = 3

Power Iteration 2 = (1 + 4 + 2 + 1) / 4 = 2

Average Power per Iteration = 2.5

Notes

The Power rating will fall within the range of your complexity rating. So if you rate task complexity on a scale of 1 to 4, then the highest possible Power rating is 4 and the lowest is 1.

A higher Power rating means that a coder has completed a higher percentage of complex tasks than others. This does not necessarily mean that the coder completed a higher number of complex tasks. For example, see Table 4-4. Coders who complete the most high complexity tasks may end up with lower Power ratings if they also complete more low complexity tasks than other coders.

Table 4-4. Coders who complete ...