DSA Discussion

dsaDiscussion.md

Discussion questions about DSA and Algorithims in Javascript

1. Discuss the concept of recursion in programming. How does it work, and in what scenarios might recursion be more advantageous than iterative solutions?
2. Explain the difference between time complexity and space complexity in algorithms. Why is it important to consider both when evaluating the efficiency of an algorithm?
3. What distinguishes linear data structures from non-linear data structures? Provide examples and use cases where one might be preferred over the other.
4. Discuss difference between linear and binary search
5. In your own words explain the following data structures:

• Linked List
• Stack
• Queues

Lentsoana Hophney
Pamela Gwala
Nokulunga Msabala

1. Recursion technique where a function calls itself to solve a problem until a base case is reached. mostly used when you have a complex code that performs the same operation over and over again and allows us to call the function instead of creating multiple functions that perform the same operations.
2. Time complexity is a function that describes how long an algorithm takes in terms of the quantity of input it receives. Space complexity is a function that describes how much memory (space) an algorithm requires to the quantity of input to the method.
   importance as to why consider both:
   -Considering both time complexity and space complexity when analyzing the efficiency of an algorithm provides a comprehensive understanding of its performance characteristics
3. Linear data structure - organize data elements sequentially, where each element is connected to its previous and next adjacent element.
   Examples:
   Array: Stores elements of the same type with indices (e.g., storing prices of cars).
   Stack: Follows the LIFO (Last In, First Out) rule (e.g., managing function calls or undo operations).

Non-linear data structures arrange data elements hierarchically, where elements are not connected sequentially.
Examples:
Trees: Hierarchical structure with a root node and child nodes (e.g., file systems, organization charts).
Graphs: Consist of nodes (vertices) connected by edges (e.g., social networks, transportation networks).

4.Linear Search sequentially checks each element in the list until it finds a match or exhausts the list
Binary Search continuously divides the sorted list, comparing the middle element with the target value
5.
A linked list is a data structure consisting of a sequence of elements, called nodes, where each node contains a reference (or link) to the next node in the sequence.
A stack is a fundamental data structure in computer science that follows the Last In, First Out (LIFO) principle.
A queue is another fundamental data structure in computer science, following the First In, First Out (FIFO) principle.
stack

Room 3- Keketso, Emihle, Nhlanhla

1. Recursion in programming is a method where a function calls itself repeatedly until it reaches a base case that stops the recursion. Recursion is particularly advantageous when dealing with problems that can be naturally broken down into smaller parts. examples of data strucutres that recursion works is in tree or graph traversal.

2. Time complexity refers to the amount of time and algorithm it takes to complete the problem, and space complexity refers to the amount of memory it requires to solve a given problem.Making sure that an algorithm is both fast and doesn't use up too much memory is important, especially in places where there isn't a lot of space or when dealing with big sets of data. Algorithms often have tradeoffs between time and space complexity optimising one aspect while compromising the other.

3. Linear - data strucutres where data is arranged linearly / sequentially where each an every element is attached to its previous and next adjacent.
   Non- linear : data strucutres where data elements are not arranged linearly/sequentially.

4. Linear It defines a sequential search algorithm, and searches until it finds what its looking for. For binary search, a sorted array is divided into two, itworks by repeatedly dividing the search interval in half until the target element is found or the interval is empty.

5. A linked list- A data structure in which sequence of notes are connected through pointers.
   Stack - A data strucutre that follows the last-in-first-out principle.
   Queues - A data structure that follows the first-in-first-out principle.

Answers.

1. It is a function that that calls itself repeatedly.

2. Time Complexity- Refers to the amount of time it takes for the algorithm to complete its execution
   Space Complexity- The amount of memory that it uses during its execution
   We are trying to find a balance between the two and to pick the best algorithm for different situations.

3. Linear data structures-It aligns data in a linear sequence, examples include arrays, lists or queues
   Non- linear data structure connects two or more information items, examples include a graph and a tree.

4. Linear checks each element until it finds the element that it is looking for and the binary search it divides the list into half and searches for the element.

5. Linked List- it is a series of nodes that are linked together through pointers.
   Stack- It is a data structure that uses the last in first out method where elements are added and
   removed from the top of the stack, allowing for efficient insertion and deletion operations.
   Queue- It is a data structure that uses that first in first out. You add elements to the end of the queue and you remove them the front.

Breakout room (Phamela, Letago, Vuyo, Koni)

Group members: Tumelo, Lindokuhle, Wesley
1)Its a process whereby a function calls itself until a certain condition is met. scenarios that would be more advantageous would be is where readability is important, e.g. Tree structures
2)Time complexity is the amount time an algorithm takes to run its execution. Space complexity the amount of space it takes to execute a function.
3)linear data structures e.g.arrays,linked lists, stack follow a sequential order while non-linear data structures is more complex and have hierachical relationships
4)linear search:
5)

1. Recursion is when the function is calling itself, it is also used to solve problems that contain smaller sub-problems. Moreover, Recursion is a programming technique where a function calls itself repeatedly until it reaches a base case that stops the recursion. In other words, a function solves a problem by breaking it down into smaller sub-problems of the same type, and then solving those sub-problems using the same function.
2. Time complexity, is used to measure the amount of time required to execute the code. Space complexity, means the amount of space required to execute successfully the functionalities of the code. Both of the above complexities are measured with respect to the input parameters.
   3.Linear Data structure where data elements are arranged sequentially or linearly where each and every element is attached to its previous and next adjacent for example [list, array, stack and queue]. while Non-linear data structure, where data elements are not arranged sequentially or lineary example [map, graph and tree].
3. In linear search input data need not to be in sorted. In binary search input data need to be in sorted order.
4. • Linked List, is a collection of nodes, each containing a value and a reference to the next node. Each node is connected to its neighbors through pointers or references. Linked lists allow for efficient insertion and deletion of elements at any position.

• Stack, A stack is a linear data structure that follows the Last-In-First-Out (LIFO) principle.
• Queues, foundational concept in computer science used for storing and managing data in a specific order.