![Activity Time!
Input: arr[] = {1, 1, 2, 1, 3, 4, 5, 2, 8};
query[] = [0, 4], [1, 3] [2, 4]
The visualization
What is the output?](https://image.slidesharecdn.com/arraysqueuesstacks-250311131157-29e3e08c/85/Linear-Data-structure-Array-stacks-and-Queues-9-320.jpg)
Linear Data structure Array stacks and Queues
- 1. Linear Data Structure Feb 1, 2025
- 3. Arrays An array is a data structure consisting of a collection of elements (values or variables), each identified by at least one array index or key. Depending on the language, array types may overlap (or be identified with) other data types that describe aggregates of values, such as lists and strings.
- 4. Is the Arrays always of a fixed size? Arrays at core are of fixed size only, but most of the languages provide dynamic sized arrays using the underlying fixed sized arrays. For example, vector in C++, ArrayList in Java and list in Python. In C language, the array has a fixed size meaning once the size is given to it, it cannot be changed i.e. you can’t shrink it nor can you expand it.
- 5. Applications of Array Data Structures Below are some applications of arrays. ● Searching: If data in array is sorted, we can search an item in O(log n) time. We can also find floor(), ceiling(), kth smallest, kth largest, etc efficiently. ● Matrices: Two-dimensional arrays are used for matrices in computations like graph algorithms and image processing. ● Implementing other data structures: Arrays are used as the underlying data structure for implementing stacks and queues. ● Dynamic programming: Dynamic programming algorithms often use arrays to store intermediate results of subproblems in order to solve a larger problem. ● Data Buffers: Arrays serve as data buffers and queues, temporarily storing incoming data like network packets, file streams, and database results before processing.
- 6. Advantages of Array Data Structure ● Efficient and Fast Access: Arrays allow direct and efficient access to any element in the collection with constant access time, as the data is stored in contiguous memory locations. ● Memory Efficiency: Arrays store elements in contiguous memory, allowing efficient allocation in a single block and reducing memory fragmentation. ● Versatility: Arrays can be used to store a wide range of data types, including integers, floating-point numbers, characters, and even complex data structures such as objects and pointers. ● Compatibility with hardware: The array data structure is compatible with most hardware architectures, making it a versatile tool for programming in a wide range of environments.
- 7. Disadvantages of Array Data Structure ● Fixed Size: Arrays have a fixed size set at creation. Expanding an array requires creating a new one and copying elements, which is time-consuming and memory-intensive. ● Memory Allocation Issues: Allocating large arrays can cause memory exhaustion, leading to crashes, especially on systems with limited resources. ● Insertion and Deletion Challenges: Adding or removing elements requires shifting subsequent elements, making these operations inefficient. ● Limited Data Type Support: Arrays support only elements of the same type, limiting their use with complex data types. ● Lack of Flexibility: Fixed size and limited type support make arrays less adaptable than structures like linked lists or trees.
- 8. Linear Search Searching Array Binary Search Binary Search is a searching algorithm used in a sorted array. In this algorithm, the element is found by repeatedly dividing the search interval in half and deciding the next interval to find the element. Linear Search is defined as a sequential search algorithm that starts at one end and goes through each element of a list until the desired element or group of elements is found. Ternary Search Ternary search is a divide and conquer algorithm that can be used to find an element in an array.
- 9. Activity Time! Input: arr[] = {1, 1, 2, 1, 3, 4, 5, 2, 8}; query[] = [0, 4], [1, 3] [2, 4] The visualization What is the output?
- 10. Difference Between Stack and Queue Data Structures
- 11. Stacks A stack is a linear data structure that follows the Last In, First Out (LIFO) principle. This means that the last element added to the stack is the first one to be removed. It can be visualized as a pile of plates where you can only add or remove the top plate.
- 12. Operations on Stack Push Adds an element to the top of the stack. Pop Removes and returns the top element of the stack. Peek (or Top) Returns the top element of the stack without removing it. isEmpty Checks if the stack is empty. Size Returns the number of elements in the stack.
- 13. Use Case of Stacks The call stack in programming languages keeps track of function calls and returns. Function Call Management Expression Evaluation Backtracking Used in parsing expressions and evaluating postfix or prefix notations. Helps in algorithms that require exploring all possibilities, such as maze solving and depth-first search.
- 14. Queues A queue is a linear data structure that follows the First In, First Out (FIFO) principle. This means that the first element added to the queue is the first one to be removed. It can be visualized as a line of people waiting for a service, where the first person in line is the first to be served.
- 15. Operations on Queue Enqueue Adds an element to the end (rear) of the queue. Dequeue Removes and returns the front element of the queue. Front (or Peek) Returns the front element of the queue without removing it. isEmpty Checks if the queue is empty. Size Returns the number of elements in the queue.
- 16. Use Case of Queues Operating systems use queues to manage tasks and processes. Task Scheduling Breadth-First Search (BFS) Buffering In graph traversal algorithms, queues help in exploring nodes level by level. Used in situations where data is transferred asynchronously, such as IO buffers and print spooling.
- 17. Activity Time!