Data Structures Concepts: Lists, Dictionaries, Trees, Graphs
Lists
Ordered (different from sorted) and linear.
Duplicates allowed.
Implementation: Array list: good for iteration, resizable; add = slide to right, remove = slide to left to close gap. Linked list: nodes & pointers, no shifting, grows dynamically, good for lots of insertions/deletions.
Core operations: add(newEntry), add(pos, newEntry), remove(pos, newEntry), replace(pos, newEntry), getEntry(pos), contains(entry), toArray(), getLength – numberOfEntries, isEmpty(), clear(). Helper methods: ensureCapacity,
Data Structures and Algorithms Code Snippets
Data Structures and Algorithms Implementations
Merge Sort Implementation
The mergeSort method recursively divides the array and then merges the sorted halves.
public static void mergeSort(int[] array) {
int length = array.length;
if (length <= 1)
return;
int middle = length / 2;
int[] leftArray = new int[middle];
int[] rightArray = new int[length - middle];
int j = 0;
for (int i = 0; i < length; i++) {
if (i < middle)
leftArray[i] =Data Structure Algorithms: Linked Lists, Trees, and Hashing
SINGLY LINKED LIST
// Insert at beginning 0
Algorithm InsertAtBeginning(data)
:1. NewNode = (Node*)malloc(sizeof(Node))2. NewNode->data = data3. NewNode->next = head4. head = newNode
// Insert at endAlgorithm InsertAtEnd(data):1. NewNode = (Node*)malloc(sizeof(Node))2. NewNode->data = data3. NewNode->next = NULL4. If head == NULL:
head = newNodeElse:temp = headWhile temp->next != NULL:temp = temp->nexttemp->next = newNode;
// Insert at position Algorithm InsertAtPos(data, pos):1.
Read MoreEssential C Programming Examples: Data Structures & Algorithms
Fundamental C Operations (String and Math)
String Reversal Without Built-in Functions
This program demonstrates manual string reversal using pointers and loops, calculating the string length without relying on strlen().
#include <stdio.h>
#include <string.h>
int main() {
char str[100], original[100];
char *start, *end, temp;
int length = 0;
printf("Enter a string: ");
scanf("%s", str); // accepts string without spaces
strcpy(original, str); // keep a copy of original Power BI Data Modeling: Star Schema, Normalization & KPIs
Flat Table
A Flat Table stores all data in a single table. It is simple and quick to build, making it suitable for very small or basic analyses. However, it leads to duplicated data, which increases the risk of errors and inconsistencies. As the dataset grows, performance and scalability worsen. For this reason, flat tables are not recommended for advanced or professional Power BI reports.
Relational Model
A Relational Model organizes data into multiple tables connected through keys. This structure
Read MoreData Structures and Algorithms Exam Review
1) Recurrences
1.1 10-mark: Solve T(n)=2T(n/2)+n, T(1)=c
T(n)=2T(n/2)+n
=4T(n/4)+2n
=8T(n/8)+3n
… after i steps: T(n)=2i T(n/2i) + i*n
Stop: n/2i=1 => i=log2 n
T(n)=n*T(1) + n log2 n = n*c + n log2 n
=> T(n)=Θ(n log n)
1.2 Master Theorem (Write As-Is)
T(n)=aT(n/b)+f(n), compare f(n) with nlogb a
- Case 1: f(n)=O(nlogb a – ε) => T(n)=Θ(nlogb a)
- Case 2: f(n)=Θ(nlogb a logk n) => T(n)=Θ(nlogb a logk+1 n)
- Case 3: f(n)=Ω(nlogb a + ε) and a f(n/b) ≤ c f(n) (c<1) => T(n)=Θ(f(n))