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Saturday, June 6, 2020

Thursday, June 4, 2020

RED BLACK TREE INSERTION STEP BY STEP EXPLANATION


RED BLACK TREE INSERTION STEP BY STEP EXPLANATION



DYSTRAS ALGORITHM OR DIJKSTRAS ALGORITHM STEP BY STEP EXPLANATION

DYSTRAS ALGORITHM OR DIJKSTRAS ALGORITHM STEP BY STEP EXPLANATION


PRIMS ALGORITHM EXPLANATION STEP BY STEP




KRUSKAL ALGORITHM EXPLANATION STEP BY STEP

KRUSKAL ALGORITHM EXPLANATION STEP BY STEP


HEAP SORT ALGORITHM STEP BY STEP EXPLANATION


HEAP SORT ALGORITHM STEP BY STEP EXPLANATION


QUICK SORT algorithm implementation example step by step


QUICK SORT algorithm implementation example step by step


selection sort example step by step


selection sort example step by step explanation



🎯 What is Selection Sort?

Selection Sort is a simple sorting algorithm that repeatedly selects the smallest element from the unsorted part of the array and places it at the beginning.


📌 Definition

Selection Sort is a comparison-based sorting algorithm in which the smallest element is selected from the unsorted portion and swapped with the first unsorted element.


🧠 How Selection Sort Works

Steps:

  1. Find the smallest element in the array
  2. Swap it with the first element
  3. Move to next position
  4. Repeat for remaining unsorted part
  5. Continue until array is sorted

📊 Example

Unsorted Array:

A = [64, 25, 12, 22, 11]

🔁 Pass 1

Smallest = 11

Swap with first element:

[11, 25, 12, 22, 64]

🔁 Pass 2

Remaining array: [25, 12, 22, 64]

Smallest = 12

[11, 12, 25, 22, 64]

🔁 Pass 3

Remaining array: [25, 22, 64]

Smallest = 22

[11, 12, 22, 25, 64]

🔁 Pass 4

Remaining array: [25, 64]

Already in order

[11, 12, 22, 25, 64]

📌 Final Sorted Array

[11, 12, 22, 25, 64]

💻 Algorithm (Pseudocode)

SelectionSort(A, n)

1. for i = 0 to n-1
2. minIndex = i
3. for j = i+1 to n-1
4. if A[j] < A[minIndex]
5. minIndex = j
6. swap(A[i], A[minIndex])

🐍 Python Program for Selection Sort

def selection_sort(arr):
n = len(arr)

for i in range(n):
min_index = i

for j in range(i + 1, n):
if arr[j] < arr[min_index]:
min_index = j

arr[i], arr[min_index] = arr[min_index], arr[i]

return arr

# Example
arr = [64, 25, 12, 22, 11]

result = selection_sort(arr)

print("Sorted Array:", result)

Output:

Sorted Array: [11, 12, 22, 25, 64]

⚡ Time Complexity

CaseComplexity
Best CaseO(n²)
Worst CaseO(n²)
Average CaseO(n²)

📊 Space Complexity

  • O(1) (in-place sorting)

🆚 Selection Sort vs Bubble Sort

FeatureSelection SortBubble Sort
MethodSelect minimumSwap adjacent
SwapsFewer swapsMany swaps
SpeedSlightly fasterSlower
Stability❌ Not stable✅ Stable
ComplexityO(n²)O(n²)

📌 Advantages

  • Simple to understand
  • Performs fewer swaps than bubble sort
  • Works in-place (no extra memory)

❌ Disadvantages

  • Very slow for large data sets
  • Always O(n²) time complexity
  • Not stable sorting algorithm

🧠 Real Life Example

  • Selecting smallest student roll number and placing first 🧑‍🎓
  • Sorting cards by repeatedly picking smallest card 🃏

📌 Summary

  • Selection sort selects the smallest element repeatedly
  • Places it at the correct position
  • Performs O(n²) comparisons
  • Efficient for small datasets only

❓ Important Questions

Short Questions

  1. What is selection sort?
  2. What is the main idea of selection sort?
  3. What is time complexity of selection sort?
  4. Is selection sort stable?
  5. How many swaps are used in selection sort?

Long Questions

  1. Explain selection sort with example.
  2. Write algorithm of selection sort.
  3. Write Python program for selection sort.
  4. Compare selection and bubble sort.
  5. Explain advantages and disadvantages of selection sort. 

RECURSIVE MERGE SORT example and recursion tree

RECURSIVE MERGE SORT example and recursion tree


BFS algorithm step by step

BFS algorithm step by step explanation


DFS algorithm step by step example

DFS algorithm step by step example


Tuesday, June 2, 2020

SZE INSTRUCTION

SZE INSTRUCTION

SZA INSTRUCTION

SZA INSTRUCTION

SNA INSTRUCTION

SNA INSTRUCTION

SPA INSTRUCTION


SPA INSTRUCTION



ISZ INSTRUCTION

  ISZ INSTRUCTION

MORRIS MANO ASSEMBLY LEVEL LANGUAGE

INSERTION SORT ALGORITHM STEP BY STEP

INSERTION SORT ALGORITHM STEP BY STEP

🎯 What is Insertion Sort?

Insertion Sort is a simple sorting algorithm that builds the final sorted array one element at a time by inserting each element into its correct position in the already sorted part.


📌 Definition

Insertion Sort is a comparison-based algorithm in which each element is picked and inserted into its correct position in a sorted subarray.


🧠 How Insertion Sort Works

Steps:

  1. Start from the second element
  2. Compare it with elements before it
  3. Shift larger elements one position right
  4. Insert the element in correct position
  5. Repeat for all elements

📊 Example

Unsorted Array:

A = [12, 11, 13, 5, 6]

🔁 Step-by-step


Pass 1 (Insert 11)

Compare 11 with 12 → shift 12

[11, 12, 13, 5, 6]

Pass 2 (Insert 13)

Already in correct position

[11, 12, 13, 5, 6]

Pass 3 (Insert 5)

Shift 13, 12, 11

[5, 11, 12, 13, 6]

Pass 4 (Insert 6)

Shift 13, 12, 11

[5, 6, 11, 12, 13]

📌 Final Sorted Array

[5, 6, 11, 12, 13]

💻 Algorithm (Pseudocode)

InsertionSort(A, n)

1. for i = 1 to n-1
2. key = A[i]
3. j = i - 1
4. while j >= 0 AND A[j] > key
5. A[j + 1] = A[j]
6. j = j - 1
7. A[j + 1] = key

🐍 Python Program for Insertion Sort

def insertion_sort(arr):
for i in range(1, len(arr)):
key = arr[i]
j = i - 1

while j >= 0 and arr[j] > key:
arr[j + 1] = arr[j]
j -= 1

arr[j + 1] = key

return arr

# Example
arr = [12, 11, 13, 5, 6]

result = insertion_sort(arr)

print("Sorted Array:", result)

Output:

Sorted Array: [5, 6, 11, 12, 13]

⚡ Time Complexity

CaseComplexity
Best CaseO(n)
Worst CaseO(n²)
Average CaseO(n²)

📊 Space Complexity

  • O(1) (in-place sorting)

🆚 Insertion Sort vs Other Sorting

FeatureInsertion SortBubble SortSelection Sort
MethodInsert element in correct positionSwap adjacent elementsSelect minimum element
Best CaseO(n)O(n)O(n²)
EfficiencyGood for small/nearly sorted dataPoorPoor
Stability✅ Stable✅ Stable❌ Not stable

📌 Advantages

  • Simple to implement
  • Efficient for small or nearly sorted data
  • Stable sorting algorithm
  • Works in-place (no extra memory)

❌ Disadvantages

  • Slow for large datasets
  • O(n²) complexity in worst case

🧠 Real Life Example

  • Arranging playing cards in hand 🃏
  • Inserting a new book in a sorted bookshelf 📚

📌 Summary

  • Insertion Sort builds a sorted list step by step
  • Each element is inserted in correct position
  • Best performance when data is already nearly sorted
  • Simple but not suitable for large datasets

❓ Important Questions

Short Questions

  1. What is insertion sort?
  2. What is key element in insertion sort?
  3. What is best case complexity?
  4. Is insertion sort stable?
  5. Give one real-life example.

Long Questions

  1. Explain insertion sort with example.
  2. Write algorithm of insertion sort.
  3. Write Python program for insertion sort.
  4. Compare insertion sort with bubble and selection sort.
  5. Explain advantages and disadvantages of insertion sort.

RADIX SORT ALGORITHM STEP BY STEP

RADIX SORT ALGORITHM STEP BY STEP


SEARCHING ALGORITHM

1. LINEAR SERACH ALGORITHM - CLICK HERE
2. BINARY SEARCH ALGORITHM - CLICK HERE

BINARY SEARCH ALGORITHM STEP BY STEP

BINARY SEARCH ALGORITHM STEP BY STEP

🎯 What is Binary Search?

Binary Search is a fast searching technique used to find an element in a sorted array by repeatedly dividing the search space into half.


📌 Definition

Binary Search is a divide-and-conquer algorithm that finds an element in a sorted list by comparing the target value with the middle element.


⚠️ Important Condition

✔ The array must be sorted (ascending or descending)
❌ Binary search does NOT work on unsorted data


🧠 How Binary Search Works

Steps:

  1. Find middle element
  2. Compare middle element with target
  3. If match → stop
  4. If target is smaller → search left half
  5. If target is larger → search right half
  6. Repeat until found or range becomes empty

📊 Example

Sorted Array:

A = [10, 20, 30, 40, 50, 60, 70]

Target:

Find 50

Step-by-step:

StepLowHighMidValueAction
10634050 > 40 → right half
24656050 < 60 → left half
344450✅ Found

💻 Algorithm (Pseudocode)

BinarySearch(A, key)

1. low = 0
2. high = n - 1

3. while low <= high
4. mid = (low + high) / 2
5. if A[mid] == key
6. return mid
7. else if key < A[mid]
8. high = mid - 1
9. else
10. low = mid + 1

11. return -1

🐍 Python Program for Binary Search

def binary_search(arr, key):
low = 0
high = len(arr) - 1

while low <= high:
mid = (low + high) // 2

if arr[mid] == key:
return mid
elif key < arr[mid]:
high = mid - 1
else:
low = mid + 1

return -1

# Example
arr = [10, 20, 30, 40, 50, 60, 70]
key = 50

result = binary_search(arr, key)

if result != -1:
print("Element found at index:", result)
else:
print("Element not found")

Output:

Element found at index: 4

⚡ Time Complexity

CaseComplexity
Best CaseO(1)
Worst CaseO(log n)
Average CaseO(log n)

📊 Why Binary Search is Fast?

Each step reduces search space by half:

Example:

  • 8 elements → 4 → 2 → 1

So it grows very slowly compared to linear search.


🆚 Binary Search vs Linear Search

FeatureLinear SearchBinary Search
Data RequirementUnsortedSorted
SpeedSlow (O(n))Fast (O(log n))
MethodSequentialDivide & Conquer
EfficiencyLowHigh

📌 Advantages of Binary Search

  • Very fast for large datasets
  • Reduces comparisons drastically
  • Efficient algorithm

❌ Disadvantages

  • Requires sorted data
  • Not suitable for dynamic/unsorted lists
  • More complex than linear search

🧠 Real Life Example

  • Finding a word in dictionary 📖
  • Searching a name in sorted telephone directory 📞

📌 Summary

  • Binary search works only on sorted data.
  • It divides the list into halves repeatedly.
  • It is much faster than linear search.
  • Time complexity is O(log n).

❓ Important Questions

Short Questions

  1. What is binary search?
  2. What is the condition for binary search?
  3. What is time complexity of binary search?
  4. What is mid element?
  5. Give one real-life example.

Long Questions

  1. Explain binary search with example.
  2. Write algorithm of binary search.
  3. Write Python program for binary search.
  4. Compare linear and binary search.
  5. Explain time complexity of binary search.

LINEAR SEARCH ALGORITHM STEP BY STEP

LINEAR SEARCH ALGORITHM STEP BY STEP

🎯 What is Linear Search?

Linear Search is a simple searching technique used to find an element in a list or array by checking each element one by one from the beginning to the end.


📌 Definition

Linear Search is a sequential searching algorithm where each element is compared with the target value until a match is found or the list ends.


🧠 How Linear Search Works

  • Start from the first element
  • Compare each element with the target value
  • If match found → Stop
  • If not found → Move to next element
  • Continue until end of list

📊 Example

Array:

A = [10, 25, 30, 45, 60]

Target:

Find 30

Step-by-step Process:

StepElement CheckedResult
110Not match
225Not match
330✅ Match found

💻 Algorithm (Pseudocode)

LinearSearch(A, n, key)

1. for i = 0 to n-1
2. if A[i] == key
3. return i
4. return -1

🐍 Linear Search Program (Python)

def linear_search(arr, key):
for i in range(len(arr)):
if arr[i] == key:
return i
return -1

# Example
arr = [10, 25, 30, 45, 60]
key = 30

result = linear_search(arr, key)

if result != -1:
print("Element found at index:", result)
else:
print("Element not found")

Output:

Element found at index: 2

⚡ Best Case, Worst Case

CaseConditionComplexity
Best CaseElement at first positionO(1)
Worst CaseElement at last or not presentO(n)
Average CaseRandom positionO(n)

📌 Advantages of Linear Search

  • Very simple to understand
  • Works on unsorted data
  • No extra memory required

❌ Disadvantages

  • Slow for large data sets
  • Not efficient compared to binary search

🆚 Linear Search vs Binary Search

FeatureLinear SearchBinary Search
Data RequirementUnsortedSorted
SpeedSlowFast
MethodSequentialDivide & Conquer

🧠 Real Life Example

  • Searching a name in attendance register
  • Finding a contact in phone list (unsorted)

📌 Summary

  • Linear search checks elements one by one.
  • It is simple but inefficient for large data.
  • Best used for small or unsorted datasets.

❓ Important Questions

Short Questions

  1. What is linear search?
  2. What is time complexity of linear search?
  3. Give one advantage of linear search.
  4. Is sorting required in linear search?
  5. Write one real-life example.

Long Questions

  1. Explain linear search with example.
  2. Write algorithm of linear search.
  3. Write a program for linear search.
  4. Compare linear and binary search.
  5. Explain best and worst case of linear search.

GRAPH THEORY

1. GRAPH THEORY ALGORITHMS - CLICK HERE

2. GRAPH THEORY N.DEO CHAPTER WISE QUESTION - CLICK HERE


GRAPH THEORY ALGORITHMS

 1. DEPTH FIRST SEARCH - CLICK HERE
 2. BREADTH FIRST SEARCH - CLICK HERE
 3. FLOYD ALGORITHM - 
 4. WARSHALL ALGORITHM - 
 5. PRIM'S ALGORITHM - CLICK HERE
 6. KRUSKAL'S ALGORITHM -CLICK HERE
 7. DYSTRA'S ALGORITHM -  CLICK HERE

BREADTH FIRST SEARCH ( BFS) ALGORITHM IMPLEMENTATION STEP BY STEP

BREADTH  FIRST SEARCH ( BFS) ALGORITHM IMPLEMENTATION STEP BY STEP


DEPTH FIRST SEARCH ( DFS) ALGORITHM IMPLEMENTATION STEP BY STEP

DEPTH FIRST SEARCH ( DFS) ALGORITHM IMPLEMENTATION STEP BY STEP