8. A system for converting applications, comprising: a processor configured to execute: a cluster component that divides application code into clusters, the application code is from a source application and written in a first programming framework; a scoring component that evaluates clusters according to predetermined programming rules wherein the scoring component is configured to: determine a conversion score for each cluster, and compare the conversion score of each cluster to a predetermined threshold score; a conversion component that converts clusters having a conversion score above the predetermined threshold into a second programming framework, an extraction component configured to: extract software features of each cluster having a score below the predetermined threshold, and pass the software features into a modeling component; and the modeling component that outputs clusters of code performing the software features in the second programming framework.
8. A system for converting applications, comprising: a processor configured to execute: a cluster component that divides application code into clusters, the application code is from a source application and written in a first programming framework; a scoring component that evaluates clusters according to predetermined programming rules wherein the scoring component is configured to: determine a conversion score for each cluster, and compare the conversion score of each cluster to a predetermined threshold score; a conversion component that converts clusters having a conversion score above the predetermined threshold into a second programming framework, an extraction component configured to: extract software features of each cluster having a score below the predetermined threshold, and pass the software features into a modeling component; and the modeling component that outputs clusters of code performing the software features in the second programming framework. 9. The system of claim 8 , comprising: a parsing component that divides the application code using k-mean clustering to create coarse logical clusters; and a hierarchy component that applies hierarchical divisive clustering to each coarse logical cluster to create fine grained micro clusters, the micro clusters are organized into type and nature of software features.