Data Structure and Programming Languages
All high level languages share a set of intercepted framework of data structure that composes the languages. These common data structures are strings, arrays, I/O, Stacks, Queues, Linked Lists, Trees, Graphs, Hash tables, and Vectors. Depending on the architectural purposes of the high level languages, these data structures are more sophisticated in design and more expressive in the languages whose purposes are more defined or drawn out toward calculating a set of problems. A programmer must possess an adept knowledge of a programming language data structure in order to fully explore all of the properties of the language in the implementation of an application. Each computer programming language that was ever designed belongs to one of these classes of paradigm that defines its purpose: imperative, object-oriented, event-driven, concurrent, distributed, generic, array-oriented, procedural, reflective, and functional. An imperative paradigm is synonymous with procedural paradigm, which is the concept that each statement is computed up and down and each state changes the state of the programs to arrive at the desire dresults. The Object Oriented Paradigm of course breaks down each sub-problem and finds their commonality and treats them as objects that can be encapsulated and modularized.
Each of these paradigms is expressed in each programming languages for the purpose of solving different problem domain that often arises in the field of computer programming.