Using discovery to create an architecture-based implementation baseline

The concept about the importance of a labeled construct being inversely related to its frequency of occurrence enables us to index entire bodies of information. The concept applying statistical tests enables us to gather similar information, cluster it, and examine it for completeness. In the process of indexing, clustering, and examining information sets, we can enforce the semantics of architecture to further refine the concept index and reuse this to iterate to a semantically complete implementation baseline description. Further, with the addition of tagging, we can provide traceability to the authoritative and original data that was used to create the implementation baseline. With the integration of the semantics of architecture, the frequency of occurrence and the statistical testing, we can create a semantically complete and semantically rich information baseline that is holistic, structured and reusable. Further, we may use this to develop rich lessons learned models, rule environments and behavioral descriptions. The model becomes the labeled anchors to the knowledge of the system.