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Further, there are "good ways" and "bad ways" to encode information.Good ways allow the computer to easily "compute" new information.The core of what good programmers do is being able to define the steps necessary to accomplish a goal.
By "ecapsulating" what is meant by "draw square" and "reusing" this operation over and over again, we make programming tractable.
The idea behind encapsulation is to store the information necessary to a particular idea in a set of variables associated with a single "object".
An algorithm (see Algorithm) is a set of specific steps to solve a problem.
Think of it this way: if you were to tell your 3 year old neice to play your favorite song on the piano (assuming the neice has never played a piano), you would have to tell her where the piano was, and how to sit on the bench, and how to open the cover, and which keys to press, and which order to press them in, etc, etc, etc.
This is prior learning (or a practical skill) that is required before enrolment on this module.
While the prior learning is expressed as named NCI module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
It is combined with another fancy term: "Abstraction". For example, a forest is really a vastly complex ecosystem containing trees, animals, water paths, etc, etc, etc.
But to a computer scientist (and to a normal person), its just "a forest".
1.1: Describe the process of program translation from source code to intermediate or executable representation 1.2: Describe the concepts of syntax and semantics of a programming language 1.3: Describe and compare rules associated with declarations, including scope and lifetime, for program constructs such as variables, functions, and methods 1.4: Describe the data representation commonly used for integers, floating point values, booleans, characters, and strings 1.5: Format and comment source code that adheres to a given set of formatting guidelines 1.6: Use command line tools to invoke the compiler and compiled executables 1.7: Use an Integrated Development Environment (IDE) to write computer programs 2: Identify and eliminate errors in programs 2.1: Describe the difference between a compiler error, run-time error, and logic error 2.2: Read errors reported by the compiler and use those error messages to correct the syntax 2.3: Use techniques and tools for debugging programs 2.4: Design and document a complete set of test cases and use this to identify logic errors 2.5: Read and analyze code written by others, and identify errors in that code 3: Specify, trace, and implement programs written in a contemporary programming language that solve a stated problem in a clean and robust fashion 3.1: Select appropriate primitive data types to represent information 3.2: Trace and use the common arithmetic operators within expressions that use parentheses and operator precedence 3.3: Describe, trace, and implement programming control structures including pretest and posttest loops, counter-controlled loops, and conditionals 3.4: Use control structures, nested and un-nested 3.5: Use console and file input and output in a program 3.6: Use one-dimensional and two-dimensional arrays 3.7: Use 3rd party class definitions, including those that represent strings, produce random numbers, perform math functions, format strings, perform console input and output, and Array Lists 4: Solve programming problems using a procedural approach 4.1: Create and implement an algorithmic approach to a problem using functional decomposition 4.2: Determine necessary/desirable functions along with their needed structure (parameters, return types, etc.) 5: Describe, trace, and implement basic algorithms 5.1: Describe, trace, and implement linear search, non-recursive binary search, and at least one non-recursive sorting algorithm 5.2: Use standard library routines for searching and sorting arrays 5.3: Compare algorithms with respect to their efficiency, elegance, and readability 6: Apply and communicate information that they read from technical sources such as APIs.
Revised to reflect the most current issues in the programming industry, this widely adopted text emphasizes that problem solving is the same in all computer languages, regardless of syntax.