7. A system for extracting knowledge embedded in source code of an application, the system comprising: a processor; a non-transitory computer readable medium; a contextual pattern decoder engine configured for receiving the source code in a programming language; a pattern conversion engine configured for extracting a plurality of knowledge elements from the source code based on predefined patterns, and determining knowledge attributes for the extracted knowledge elements based on target specification attributes of a desired target architecture, wherein the contextual pattern decoder engine is further configured for subdividing the knowledge elements using predefined decoding patterns; a pattern hatcher engine configured for creating, responsive to no predefined decoding pattern matching a knowledge element, a decoding pattern using fuzzy rules and subdividing the knowledge element using the new decoding pattern; and a pattern abstraction engine configured for generating an abstract representation of the source code in a format appropriate for the desired target architecture independent of the programming language of the source code, wherein the abstract representation includes the plurality of knowledge elements, wherein the pattern hatcher engine is further configured for hatching a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a contextual taxonomy store segment, and wherein the pattern conversion engine is further configured for identifying the knowledge attributes for the included knowledge elements in the abstract representation.
7. A system for extracting knowledge embedded in source code of an application, the system comprising: a processor; a non-transitory computer readable medium; a contextual pattern decoder engine configured for receiving the source code in a programming language; a pattern conversion engine configured for extracting a plurality of knowledge elements from the source code based on predefined patterns, and determining knowledge attributes for the extracted knowledge elements based on target specification attributes of a desired target architecture, wherein the contextual pattern decoder engine is further configured for subdividing the knowledge elements using predefined decoding patterns; a pattern hatcher engine configured for creating, responsive to no predefined decoding pattern matching a knowledge element, a decoding pattern using fuzzy rules and subdividing the knowledge element using the new decoding pattern; and a pattern abstraction engine configured for generating an abstract representation of the source code in a format appropriate for the desired target architecture independent of the programming language of the source code, wherein the abstract representation includes the plurality of knowledge elements, wherein the pattern hatcher engine is further configured for hatching a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a contextual taxonomy store segment, and wherein the pattern conversion engine is further configured for identifying the knowledge attributes for the included knowledge elements in the abstract representation. 8. The system of claim 7 , wherein the contextual pattern decoder engine is further configured for deriving a data entity life cycle or a data variable life cycle from the source code using a dynamic rule.