From: Investigating measures for applying statistical process control in software organizations
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 related to a critical process. | |
R5. The measure must be able to describe the process behavior. | |
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 for analysis must be defined. | |
R12. Data collected for the measure must include context information. | |
R13. Data collected for the measure must be accessible and retrievable. | |
R14. The measure should not consider aggregate data (or if it does, it should be possible to disaggregate them). | |
R15. Data collected for the measure must be consistent. | |
R16. Data collected for the measure must be precise. | |
R17. The amount of collected data must be enough for applying SPC techniques. |