Contextualization and Abstraction 

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... language should be the vehicle of abstraction; it should be simple, robust and complete to be more robust. This is achieved by hiding its complexity levels, using layers. The first layer covers a formal level which supports and extends mechanisms already developed and recognized such as encapsulation, security, generality, reuse, among others [1]. The second layer covers a particular level ease of use, focused on approaching the model and reality, taking in account the human thinking model. To address these concerns, the paper presents the CFL language, its grammar, the comparison between schema and diagram, principles and metrics, closing with the implementation of the platform, case studies, and conclusions. CFL, is a modeling language focused on abstraction and contextualization of knowledge. See Fig. 1. When communicating an idea, this language can be used in both ways, spoken or written. Treasures such as the Rosetta Stone [2], unveiled a past steeped in pictograms; rock art paintings tell about the lives of our ancestors, in images that constitute a simple but expressive language. The language can range from an informal expression, captured in an image, to the rigorous expression represented in a word or syntactic structure. The CFL proposal is to exploit the power of formal language with the power of symbolic schematization, for that, it proposes two concepts, abstraction and contextualization. The abstraction mechanism extracts the essential characteristics, using cognitive models like: paradigms, values, principles and behaviors; abstraction uses introspection as strategy which defines the search mechanisms stock of knowledge in the same individual.. Moreover, contextualization uses an observation scheme to find the answers in external phenomena. The strategy used is immersion, which in contrast to introspection, seeks to reason about the phenomena through the use of external structures. Contextualization and abstraction are the basis for CFL construction, in which individual and collective knowledge are contrasted. Paradigms as “structured”, “object -oriente d”, including “declarative models” are based on abstraction [3], losing the potential of immersion, useful in solution modeling. Next, the concepts of grammar, derivation (production) and language are defined, all primordial for CFL formalization. A phrase structure grammar G = (V, T, S, P) consists of a vocabulary V ∗ , a subset T of V ∗ formed by the terminal elements, and a initial symbol S of V– T and a set P of productions. The V– T set is denoted by N . The elements of N are called nonterminal elements [4]. Furthermore, a vocabulary V (or alphabet) is a finite and non empty set, whose elements are called symbols, a word in V is a finite string of V elements. The empty word or empty string denoted by λ is the string without symbols. The set of all words about V is denoted by V ∗ . A language in V is a subset of V ∗ [4]. Another important definition is the derivation: G = (V, T, S, P) is a grammar with sentence structure. Also w 0 = lz 0 r (this is a concatenation lz 0 y r ) and w 1 = lz 1 r about V . If z 0 → z 1 is a production of G , we say that w 1 , is directly derived from w 0 , and we write w 0 ⇒ w 1 . If w 0 , w 1 , ... w n are strings about V such that w 0 ⇒ w 1 , w 1 ⇒ w 2 ... , w n−1 ⇒ w n we say that w n is derivable or is ∗ derived from w 0 and will be denoted w 0 ⇒ w n . The sequence of steps used to obtain w n from w 0 is called derivation [4]. Finally, the language generated by G (or the G language) must be defined, denoted by L(G) , as the set of all terminal strings derived from initial state S , Equation 1. ...