Imperative Programming Parts 1 and 2

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Key Features

Its benefits include being simple to learn and read, having an easy mental paradigm, and so on.

Imperative programming is a form of programming paradigm that describes the processes that computers should take to accomplish or achieve an objective.

It permits functions to be viewed as special case constructs because whole method calls are rarely returned from a method in imperative programming.

Its benefits include being simple to learn and read, having an easy mental paradigm, and so on.

It entails creating programs in the form of a series of instructions or statements that can actively affect memory.

Through recursive function call nesting, new values are typically associated with various names.

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Key Topics

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    Imperative programming is traced from imperare, a Latin word that implies command and is one of the oldest programming paradigms. In most instances, imperative programming is made of a clearly defined sequence of instructions by specifying what the computer does and when to achieve the desired result.
    Most concepts under imperative programming parts 1 and 2 are from the functional programming unit. In this unit, the scholar is required to design programs that are written in imperative styles. Here as a programming student, you learn how to construct programs systematically, by structuring with well-defined interfaces through a collection of modules.
    Mainly, by the end of the lesson, you are required to have grasped the concept of loop invariants and reasoning about the loops. You are also needed to learn how to modularize large programs, capture the functionality of a component of the program using the specification, describing the relationship between the implementation and specification. Most of the final project’s tests were on maintaining, creating, and debugging programs.
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      • Conditionals
      • Loops
      • Procedures
    • Methods of invariants
    • Uni testing
    • Quicksort
    • Binary Search
    • Documentation and testing of objects
    • Linked lists
    • Binary trees
    • Implementation of abstract datatypes
    • Abstract datatypes and modularization
    • Bit maps and hash tables

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