Computational thinking is the thought processes
involved in formulating problems and their solutions so that the solutions are
represented in a form that can be effectively carried out by an
information-processing agent. Informally, computational thinking describes the
mental activity in formulating a problem to admit a computational solution. The
solution can be carried out by a human or machine, or more generally, by
combinations of humans and machines. Computational thinking is used in the
design and analysis of problems and their solutions, broadly interpreted. The
most important and high-level thought process in computational thinking is the
abstraction process. Abstraction is used in defining patterns, generalizing
from instances, and parameterization. It is used to let one object stand for
many. It is used to capture essential properties common to a set of objects
while hiding irrelevant distinctions among them. For example, an algorithm is
an abstraction of a process that takes inputs, executes a sequence of steps,
and produces outputs to satisfy a desired goal. An abstract data type defines
an abstract set of values and operations for manipulating those values, hiding
the actual representation of the values from the user of the abstract data
type. Designing efficient algorithms inherently involves designing abstract
data types. Abstraction gives us the power to scale and deal with complexity.
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