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DS & A (DATA STRUCUTRES)

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| CHAPTER 1 | What is Data Structures? Data Structures are any data representations and it's associated operations. It is also defined as the implementation of ADT(Abstract Data Type, We will learn about Abstract Data Type later). E.g. Integer: Summation        String: Replace Note: There are different types of data Structures and no particular data structure is better than the other in all cases, it all comes down to a number of factors depending on which a certain type of Data Structure is suitable for a certain problem. Resource Constraints such as Time consumption and space(memory) availability are the two major factors that determine the efficiency of a certain data structure. Selecting Efficient Data Structure for a problem Carefully analyze the problem and figure out the resource constraints.  Determine the basic operations and quantify the resource constraints for each operation.  Select the data structure that best meets the requirements. 
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ScaleFree

DS & A(Queue)

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|  CHAPTER 14  | In this chapter, our topic of discussion will be the "Queue" Data Structure. But, before we get started, I would recommend you to read the previous chapters on Data Structures & Algorithms  (especially the chapters on Array List , Linked List , Array Stack , and Linked Stack ), that is in case it's your first time visiting my blog. Queue: Just like Stacks, Queues also are a restricted version of List but with a few minor differences compared to Stack. The following are some of the notable characteristics of a Queue: Data can only be inserted from the rear/back. Data insertion is referred to as  ENQUEUE . Data can only be deleted from the front. Data deletion is referred to as  DEQUEUE . Alternatively,  ENQUEUE  and  DEQUEUE  should always be executed on the opposite ends of the Queue. A Queue follows the  FIFO (First In First Out)   principle. The first and the last elements are referred to as FRONT and REAR respectively.
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