31. The system of claim 24 wherein the instructions causing the processor to process the expression model to generate a logical model comprise instructions that, when executed by the processor, cause the processor to: process terms included in the expression model to associate each of the terms with a type; process a sentence form included in the expression model to associate the sentence form with a fact type; if the expression model includes a name, process the name to map the name to a type, the name corresponding to a term of the processed terms; if the expression model includes a nominal restrictive form, process the nominal restrictive form to map the nominal restrictive form to a fact type; if the expression model includes a mathematical function form, process the mathematical function form to map the mathematical function form to a fact type; if the expression model includes an identity criterion, process the identity criterion to map the identity criterion to a type; if at least one of the types has type specializations or generalizations, derive the type specializations and generalizations for the one of the types; if at least one of the types has fact type specializations or generalizations, derive the fact type specializations and generalizations for the one of the fact types; and if the expression model includes an expression, process the expression to generate a logical formulation, the expression including at least one of a name, a term, a function form having at least a placeholder, and an identity criterion.
24. A system for generating software components from one or more rule statements expressed in a natural language, the method, the system comprising: a processor; a memory coupled to the processor and the memory containing instructions that, when executed by the processor, cause the processor to: receive symbols of a vocabulary of a natural language, the natural language having grammatical rules, and details about each of the symbols; receive at least one rule statement expressed using the symbols of the vocabulary of the natural language; parse the rule statement in accordance with the natural language grammatical rules to generate a language-based structure of the rule statement that identifies the symbols used and their interrelationships with respect to a sentence structure, wherein the parsing reports how each word in the rule statement is categorized into: a) terms defined in the vocabulary, b) names defined in the vocabulary for individual things, c) connecting symbols of function forms defined in the vocabulary, d) key words and phrases, quantifiers, and logical connectives, and e) words that are not recognized; process the language-based structure of the rule statement corresponding to an expression to generate an expression model; process the expression model to generate a logical model wherein processing the expression model comprises: a) relating synonymous terms to a single concept; b) relating synonymous forms and related noun forms to a single fact type; c) relating synonymous names to a single instance; d) relating each instance to its corresponding concept; e) determining identifying fact types for concepts; f) determining generalizations between concepts; and g) reporting logical inconsistencies, if any; process the logical model to generate a platform-independent implementation model in response to a request for such generation; receive a specific target platform description; and process the platform-independent implementation model using the specific target platform description to generate a platform-specific implementation model.