August 2011
Intermediate to advanced
264 pages
8h 42m
English
Content preview from Codermetrics
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Input Data
The input data for Value Metrics is the output of Skill Metrics and Response Metrics. Table 6-1 lists the specific metrics that are used for Value Metrics. For details on these metrics, including the data required for each and the formula to calculate them, please refer to the appropriate chapter and section.
Table 6-1. Input data for Value Metrics
| Metric | Chapter | Description |
|---|---|---|
| Utility | Skill Metrics | Measures how many assigned tasks each coder completes |
| Power | Skill Metrics | Measures the average complexity of the tasks that a coder completes |
| Temperature | Skill Metrics | Measures how “hot” or “cold” a coder is at any given time |
| O-Impact | Skill Metrics | “Offensive Impact” that summarizes the contributions of a coder in moving projects along |
| Saves | Skill Metrics | Measures how often a coder helps fix urgent production issues |
| Tackles | Skill Metrics | Measures how many potential issues or opportunities a coder handles proactively |
| Range | Skill Metrics | Measures how many areas of software a coder works on |
| D-Impact | Skill Metrics | “Defensive Impact” that summarizes the contributions of a coder in helping to avoid large problems |
| Turnovers | Skill Metrics | Measures the magnitude of assigned tasks that a coder fails to complete |
| Errors | Skill Metrics | Measures the magnitude of production issues found related to areas that a coder is responsible for |
| Wins | Response Metrics | Measures the number of active users added |
| Losses | Response Metrics | Measures the number of active users lost |
| Acceleration | Response Metrics | Measures the ratio of user benefits delivered ... |
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