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Algorithmic Design & Data Structure Techniques

     Structured programs are developed using algorithmic design & data structures, solving complex problems efficiently. Understanding the Problem • Algorithmic Design: Start by breaking down complex problems into smaller subproblems using techniques like divide and conquer, greedy algorithms, or dynamic programming to understand the problem requirements. • Data Structures: Choose appropriate data structures based on problem requirements, such as using arrays for contiguous memory allocation or trees for hierarchical data representation. Selecting Suitable Algorithms and Data Structures • Algorithmic Design: Depending on the problem type (searching, sorting, optimization, etc.), choose algorithms like binary search, quicksort, or BFS/DFS for graph traversal. • Data Structures: When it comes to data structures, it's important to choose efficient ones. For example, hash tables provide constant time lookups, while balanced trees like AVL or Red-Black ...
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Object-oriented Programming

Object-oriented programming (OOP) is a programming paradigm that organizes data and behavior into reusable structures called objects. Each object contains data (often attributes or properties) and methods (functions that operate on the object’s data).   Object-oriented programming has four major principles which are, Encapsulation, Inheritance, Abstraction and Polymorphism.    Encapsulation   Encapsulation refers to combining data (attributes) and methods (functions) that operate on the data into a single unit called a class. This mechanism helps conceal the object's internal state from the outside world and enables access to data through public methods, such as getters and setters. In other words, encapsulation provides a way to keep data and methods safe and secure within the class and only allows controlled access.   Features   Data Hiding:  The data within an object is hidden and can only be accessed and modified through its public methods, ensurin...
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