From: A strategy for preparing software organizations for statistical process control
R1. The measure must be aligned to organizational or project goals |
R2. The measure must be able to support decision making |
R3. The measure must be able to support software process improvement |
R4. The measure must be associated to a critical process |
R5. The measure must be able to describe the process performance |
R6. The measure must have appropriate granularity level |
R7. The operational definition of the measure must be correct and satisfactory |
R8. The correlated measures to the measure must be defined |
R9. The measure must be correctly normalized (if applicable) |
R10. It must be possible to normalize the measure (if applicable) |
R11. The criteria for grouping data to the measure analysis must be defined |
R12. The measurement data related to the measure must include context information |
R13. The measurement data related to the measure must be accessible and retrievable |
R14. The measure must be related to the process or activity in which the measurement is carried out |
R15. The measure should not consider aggregated data |
R16. It must be possible to identify the process definition in which data were collected for the measure |
R17. The collected data for the measure must be consistent |
R18. The collected data for the measure must be precise |
R19. There is no lost data for the measure or the amount of lost data does not compromise the analysis |
R20. The amount of collected data is sufficient |