• Time Complexity of Sorting Algorithms in Python, Java, and C++

    Posted on : June 13, 2025

    By

    Tech World Times

    Development and Testing 

    Rate this post

    Sorting helps organize data in a specific order. It is used in search, reports, and efficient storage. Different sorting algorithms offer different performance. In this article, we will explain the Time Complexity of Sorting Algorithms in simple words. We will cover Python, Java, and C++ examples.
    1. What Is Time Complexity?
    Time complexity tells how fast an algorithm runs. It measures the number of steps as input grows. It is written in Big-O notation. For example, Omeans steps grow with the square of inputs.
    2. Types of Time Complexity
    Here are common types:

    O: Constant time
    O: Linear time
    O: Log-linear time
    O: Quadratic time

    We will now apply these to sorting.
    3. Bubble Sort
    Bubble Sort compares two numbers and swaps them if needed. It repeats until the list is sorted.
    Time Complexity:

    Best Case: OAverage Case: OWorst Case: OPython Example:
    pythonCopyEditdef bubble_sort:
    n = lenfor i in range:
    for j in range:
    if arr> arr:
    arr, arr= arr, arrJava Example:
    javaCopyEditvoid bubbleSort{
    int n = arr.length;
    forforif{
    int temp = arr;
    arr= arr;
    arr= temp;
    }
    }

    C++ Example:
    cppCopyEditvoid bubbleSort{
    forforifswap;
    }

    4. Selection Sort
    This sort picks the smallest number and places it at the front.
    Time Complexity:

    Best Case: OAverage Case: OWorst Case: OPython Example:
    pythonCopyEditdef selection_sort:
    for i in range):
    min_idx = i
    for j in range):
    if arr< arr:
    min_idx = j
    arr, arr= arr, arr5. Insertion Sort
    This algorithm builds the final list one item at a time.
    Time Complexity:

    Best Case: OAverage Case: OWorst Case: OJava Example:
    javaCopyEditvoid insertionSort{
    for{
    int key = arr;
    int j = i - 1;
    while{
    arr= arr;
    j = j - 1;
    }
    arr= key;
    }
    }

    6. Merge Sort
    Merge Sort splits the array into halves and merges them back in order.
    Time Complexity of Sorting Algorithms like Merge Sort is usually better.

    Best Case: OAverage Case: OWorst Case: OPython Example:
    pythonCopyEditdef merge_sort:
    if len> 1:
    mid = len// 2
    left = arrright = arrmerge_sortmerge_sorti = j = k = 0
    while i < lenand j < len:
    if left< right:
    arr= lefti += 1
    else:
    arr= rightj += 1
    k += 1

    arr= left+ right7. Quick Sort
    Quick Sort picks a pivot and places smaller numbers before it.
    Time Complexity:

    Best Case: OAverage Case: OWorst Case: OC++ Example:
    cppCopyEditint partition{
    int pivot = arr;
    int i = low - 1;
    for{
    if{
    i++;
    swap;
    }
    }
    swap;
    return i + 1;
    }

    void quickSort{
    if{
    int pi = partition;
    quickSort;
    quickSort;
    }
    }

    8. Built-in Sort Methods
    Languages have built-in sort functions. These are well-optimized.

    Python: sortedor list.sortuses TimSort

    Time Complexity: OJava: Arrays.sortuses Dual-Pivot QuickSort

    Time Complexity: OC++: std::sortuses IntroSort

    Time Complexity: OThese are better for most real-world tasks.
    9. Time Complexity Comparison Table
    AlgorithmBestAverageWorstStableBubble SortOOOYesSelection SortOOONoInsertion SortOOOYesMerge SortOOOYesQuick SortOOONoTimSortOOOYesIntroSortOOONo
    10. How to Choose the Right Algorithm?

    Use Merge Sort for large stable data.
    Use Quick Sort for faster average speed.
    Use Insertion Sort for small or nearly sorted lists.
    Use built-in sort functions unless you need control.

    Conclusion
    The Time Complexity of Sorting Algorithms helps us pick the right tool. Bubble, Selection, and Insertion Sort are simple but slow. Merge and Quick Sort are faster and used often. Built-in functions are highly optimized. Python, Java, and C++ each have their strengths.
    Understand your problem and input size. Then pick the sorting method. This ensures better speed and performance in your code.
    Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
    #time #complexity #sorting #algorithms #python
    Time Complexity of Sorting Algorithms in Python, Java, and C++
    Posted on : June 13, 2025 By Tech World Times Development and Testing  Rate this post Sorting helps organize data in a specific order. It is used in search, reports, and efficient storage. Different sorting algorithms offer different performance. In this article, we will explain the Time Complexity of Sorting Algorithms in simple words. We will cover Python, Java, and C++ examples. 1. What Is Time Complexity? Time complexity tells how fast an algorithm runs. It measures the number of steps as input grows. It is written in Big-O notation. For example, Omeans steps grow with the square of inputs. 2. Types of Time Complexity Here are common types: O: Constant time O: Linear time O: Log-linear time O: Quadratic time We will now apply these to sorting. 3. Bubble Sort Bubble Sort compares two numbers and swaps them if needed. It repeats until the list is sorted. Time Complexity: Best Case: OAverage Case: OWorst Case: OPython Example: pythonCopyEditdef bubble_sort: n = lenfor i in range: for j in range: if arr> arr: arr, arr= arr, arrJava Example: javaCopyEditvoid bubbleSort{ int n = arr.length; forforif{ int temp = arr; arr= arr; arr= temp; } } C++ Example: cppCopyEditvoid bubbleSort{ forforifswap; } 4. Selection Sort This sort picks the smallest number and places it at the front. Time Complexity: Best Case: OAverage Case: OWorst Case: OPython Example: pythonCopyEditdef selection_sort: for i in range): min_idx = i for j in range): if arr< arr: min_idx = j arr, arr= arr, arr5. Insertion Sort This algorithm builds the final list one item at a time. Time Complexity: Best Case: OAverage Case: OWorst Case: OJava Example: javaCopyEditvoid insertionSort{ for{ int key = arr; int j = i - 1; while{ arr= arr; j = j - 1; } arr= key; } } 6. Merge Sort Merge Sort splits the array into halves and merges them back in order. Time Complexity of Sorting Algorithms like Merge Sort is usually better. Best Case: OAverage Case: OWorst Case: OPython Example: pythonCopyEditdef merge_sort: if len> 1: mid = len// 2 left = arrright = arrmerge_sortmerge_sorti = j = k = 0 while i < lenand j < len: if left< right: arr= lefti += 1 else: arr= rightj += 1 k += 1 arr= left+ right7. Quick Sort Quick Sort picks a pivot and places smaller numbers before it. Time Complexity: Best Case: OAverage Case: OWorst Case: OC++ Example: cppCopyEditint partition{ int pivot = arr; int i = low - 1; for{ if{ i++; swap; } } swap; return i + 1; } void quickSort{ if{ int pi = partition; quickSort; quickSort; } } 8. Built-in Sort Methods Languages have built-in sort functions. These are well-optimized. Python: sortedor list.sortuses TimSort Time Complexity: OJava: Arrays.sortuses Dual-Pivot QuickSort Time Complexity: OC++: std::sortuses IntroSort Time Complexity: OThese are better for most real-world tasks. 9. Time Complexity Comparison Table AlgorithmBestAverageWorstStableBubble SortOOOYesSelection SortOOONoInsertion SortOOOYesMerge SortOOOYesQuick SortOOONoTimSortOOOYesIntroSortOOONo 10. How to Choose the Right Algorithm? Use Merge Sort for large stable data. Use Quick Sort for faster average speed. Use Insertion Sort for small or nearly sorted lists. Use built-in sort functions unless you need control. Conclusion The Time Complexity of Sorting Algorithms helps us pick the right tool. Bubble, Selection, and Insertion Sort are simple but slow. Merge and Quick Sort are faster and used often. Built-in functions are highly optimized. Python, Java, and C++ each have their strengths. Understand your problem and input size. Then pick the sorting method. This ensures better speed and performance in your code. Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com #time #complexity #sorting #algorithms #python
    TECHWORLDTIMES.COM
    Time Complexity of Sorting Algorithms in Python, Java, and C++
    Posted on : June 13, 2025 By Tech World Times Development and Testing  Rate this post Sorting helps organize data in a specific order. It is used in search, reports, and efficient storage. Different sorting algorithms offer different performance. In this article, we will explain the Time Complexity of Sorting Algorithms in simple words. We will cover Python, Java, and C++ examples. 1. What Is Time Complexity? Time complexity tells how fast an algorithm runs. It measures the number of steps as input grows. It is written in Big-O notation. For example, O(n²) means steps grow with the square of inputs. 2. Types of Time Complexity Here are common types: O(1): Constant time O(n): Linear time O(n log n): Log-linear time O(n²): Quadratic time We will now apply these to sorting. 3. Bubble Sort Bubble Sort compares two numbers and swaps them if needed. It repeats until the list is sorted. Time Complexity: Best Case: O(n) (if already sorted) Average Case: O(n²) Worst Case: O(n²) Python Example: pythonCopyEditdef bubble_sort(arr): n = len(arr) for i in range(n): for j in range(n - i - 1): if arr[j] > arr[j+1]: arr[j], arr[j+1] = arr[j+1], arr[j] Java Example: javaCopyEditvoid bubbleSort(int arr[]) { int n = arr.length; for (int i = 0; i < n-1; i++) for (int j = 0; j < n-i-1; j++) if (arr[j] > arr[j+1]) { int temp = arr[j]; arr[j] = arr[j+1]; arr[j+1] = temp; } } C++ Example: cppCopyEditvoid bubbleSort(int arr[], int n) { for (int i = 0; i < n-1; i++) for (int j = 0; j < n-i-1; j++) if (arr[j] > arr[j+1]) swap(arr[j], arr[j+1]); } 4. Selection Sort This sort picks the smallest number and places it at the front. Time Complexity: Best Case: O(n²) Average Case: O(n²) Worst Case: O(n²) Python Example: pythonCopyEditdef selection_sort(arr): for i in range(len(arr)): min_idx = i for j in range(i+1, len(arr)): if arr[j] < arr[min_idx]: min_idx = j arr[i], arr[min_idx] = arr[min_idx], arr[i] 5. Insertion Sort This algorithm builds the final list one item at a time. Time Complexity: Best Case: O(n) Average Case: O(n²) Worst Case: O(n²) Java Example: javaCopyEditvoid insertionSort(int arr[]) { for (int i = 1; i < arr.length; i++) { int key = arr[i]; int j = i - 1; while (j >= 0 && arr[j] > key) { arr[j + 1] = arr[j]; j = j - 1; } arr[j + 1] = key; } } 6. Merge Sort Merge Sort splits the array into halves and merges them back in order. Time Complexity of Sorting Algorithms like Merge Sort is usually better. Best Case: O(n log n) Average Case: O(n log n) Worst Case: O(n log n) Python Example: pythonCopyEditdef merge_sort(arr): if len(arr) > 1: mid = len(arr) // 2 left = arr[:mid] right = arr[mid:] merge_sort(left) merge_sort(right) i = j = k = 0 while i < len(left) and j < len(right): if left[i] < right[j]: arr[k] = left[i] i += 1 else: arr[k] = right[j] j += 1 k += 1 arr[k:] = left[i:] + right[j:] 7. Quick Sort Quick Sort picks a pivot and places smaller numbers before it. Time Complexity: Best Case: O(n log n) Average Case: O(n log n) Worst Case: O(n²) C++ Example: cppCopyEditint partition(int arr[], int low, int high) { int pivot = arr[high]; int i = low - 1; for (int j = low; j < high; j++) { if (arr[j] < pivot) { i++; swap(arr[i], arr[j]); } } swap(arr[i+1], arr[high]); return i + 1; } void quickSort(int arr[], int low, int high) { if (low < high) { int pi = partition(arr, low, high); quickSort(arr, low, pi - 1); quickSort(arr, pi + 1, high); } } 8. Built-in Sort Methods Languages have built-in sort functions. These are well-optimized. Python: sorted() or list.sort() uses TimSort Time Complexity: O(n log n) Java: Arrays.sort() uses Dual-Pivot QuickSort Time Complexity: O(n log n) C++: std::sort() uses IntroSort Time Complexity: O(n log n) These are better for most real-world tasks. 9. Time Complexity Comparison Table AlgorithmBestAverageWorstStableBubble SortO(n)O(n²)O(n²)YesSelection SortO(n²)O(n²)O(n²)NoInsertion SortO(n)O(n²)O(n²)YesMerge SortO(n log n)O(n log n)O(n log n)YesQuick SortO(n log n)O(n log n)O(n²)NoTimSort (Python)O(n)O(n log n)O(n log n)YesIntroSort (C++)O(n log n)O(n log n)O(n log n)No 10. How to Choose the Right Algorithm? Use Merge Sort for large stable data. Use Quick Sort for faster average speed. Use Insertion Sort for small or nearly sorted lists. Use built-in sort functions unless you need control. Conclusion The Time Complexity of Sorting Algorithms helps us pick the right tool. Bubble, Selection, and Insertion Sort are simple but slow. Merge and Quick Sort are faster and used often. Built-in functions are highly optimized. Python, Java, and C++ each have their strengths. Understand your problem and input size. Then pick the sorting method. This ensures better speed and performance in your code. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
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  • EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs

    Originally published at EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs by Anush Yolyan.

    The integration will deliver simple, accessible, and streamlined email security for vulnerable inboxes

    Global, 4 November 2024 – US-based email security firm EasyDMARC has today announced its integration with Pax8 Marketplace, the leading cloud commerce marketplace. As one of the first DMARC solution providers on the Pax8 Marketplace, EasyDMARC is expanding its mission to protect inboxes from the rising threat of phishing attacks with a rigorous, user-friendly DMARC solution.

    The integration comes as Google highlights the impressive results of recently implemented email authentication measures for bulk senders: a 65% reduction in unauthenticated messages to Gmail users, a 50% increase in bulk senders following best security practices, and 265 billion fewer unauthenticated messages sent in 2024. With email being such a crucial communication channel for businesses, email authentication measures are an essential part of any business’s cybersecurity offering. 

    Key features of the integration include:

    Centralized billing

    With centralized billing, customers can now streamline their cloud services under a single pane of glass, simplifying the management and billing of their EasyDMARC solution. This consolidated approach enables partners to reduce administrative complexity and manage all cloud expenses through one interface, providing a seamless billing and support experience.

    Automated provisioning 

    Through automated provisioning, Pax8’s automation capabilities make deploying DMARC across client accounts quick and hassle-free. By eliminating manual configurations, this integration ensures that customers can implement email security solutions rapidly, allowing them to safeguard client inboxes without delay.

    Bundled offerings

    The bundled offerings available through Pax8 allow partners to enhance their service portfolios by combining EasyDMARC with complementary security solutions. By creating all-in-one security packages, partners can offer their clients more robust protection, addressing a broader range of security needs from a single, trusted platform.

    Gerasim Hovhannisyan, Co-Founder and CEO of EasyDMARC, said:

    “We’re thrilled to be working with Pax8  to provide MSPs with a streamlined, effective way to deliver top-tier email security to their clients, all within a platform that equips them with everything needed to stay secure.  As phishing attacks grow in frequency and sophistication, businesses can no longer afford to overlook the importance of email security. Email authentication is a vital defense against the evolving threat of phishing and is crucial in preserving the integrity of email communication. This integration is designed to allow businesses of all sizes to benefit from DMARC’s extensive capabilities.”

    Ryan Burton, Vice President of Marketplace Vendor Strategy, at Pax8 said: 

    “We’re delighted to welcome EasyDMARC to the Pax8 Marketplace as an enterprise-class DMARC solution provider. This integration gives MSPs the tools they need to meet the growing demand for email security, with simplified deployment, billing, and bundling benefits. With EasyDMARC’s technical capabilities and intelligence, MSPs can deliver robust protection against phishing threats without the technical hassle that often holds businesses back.”

    About EasyDMARC

    EasyDMARC is a cloud-native B2B SaaS solution that addresses email security and deliverability problems with just a few clicks. For Managed Service Providers seeking to increase their revenue, EasyDMARC presents an ideal solution. The email authentication platform streamlines domain management, providing capabilities such as organizational control, domain grouping, and access management.

    Additionally, EasyDMARC offers a comprehensive sales and marketing enablement program designed to boost DMARC sales. All of these features are available for MSPs on a scalable platform with a flexible pay-as-you-go pricing model.

    For more information on the EasyDMARC, visit: /

    About Pax8 

    Pax8 is the technology marketplace of the future, linking partners, vendors, and small to midsized businessesthrough AI-powered insights and comprehensive product support. With a global partner ecosystem of over 38,000 managed service providers, Pax8 empowers SMBs worldwide by providing software and services that unlock their growth potential and enhance their security. Committed to innovating cloud commerce at scale, Pax8 drives customer acquisition and solution consumption across its entire ecosystem.

    Find out more: /

    The post EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs appeared first on EasyDMARC.
    #easydmarc #integrates #with #pax8 #marketplace
    EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs
    Originally published at EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs by Anush Yolyan. The integration will deliver simple, accessible, and streamlined email security for vulnerable inboxes Global, 4 November 2024 – US-based email security firm EasyDMARC has today announced its integration with Pax8 Marketplace, the leading cloud commerce marketplace. As one of the first DMARC solution providers on the Pax8 Marketplace, EasyDMARC is expanding its mission to protect inboxes from the rising threat of phishing attacks with a rigorous, user-friendly DMARC solution. The integration comes as Google highlights the impressive results of recently implemented email authentication measures for bulk senders: a 65% reduction in unauthenticated messages to Gmail users, a 50% increase in bulk senders following best security practices, and 265 billion fewer unauthenticated messages sent in 2024. With email being such a crucial communication channel for businesses, email authentication measures are an essential part of any business’s cybersecurity offering.  Key features of the integration include: Centralized billing With centralized billing, customers can now streamline their cloud services under a single pane of glass, simplifying the management and billing of their EasyDMARC solution. This consolidated approach enables partners to reduce administrative complexity and manage all cloud expenses through one interface, providing a seamless billing and support experience. Automated provisioning  Through automated provisioning, Pax8’s automation capabilities make deploying DMARC across client accounts quick and hassle-free. By eliminating manual configurations, this integration ensures that customers can implement email security solutions rapidly, allowing them to safeguard client inboxes without delay. Bundled offerings The bundled offerings available through Pax8 allow partners to enhance their service portfolios by combining EasyDMARC with complementary security solutions. By creating all-in-one security packages, partners can offer their clients more robust protection, addressing a broader range of security needs from a single, trusted platform. Gerasim Hovhannisyan, Co-Founder and CEO of EasyDMARC, said: “We’re thrilled to be working with Pax8  to provide MSPs with a streamlined, effective way to deliver top-tier email security to their clients, all within a platform that equips them with everything needed to stay secure.  As phishing attacks grow in frequency and sophistication, businesses can no longer afford to overlook the importance of email security. Email authentication is a vital defense against the evolving threat of phishing and is crucial in preserving the integrity of email communication. This integration is designed to allow businesses of all sizes to benefit from DMARC’s extensive capabilities.” Ryan Burton, Vice President of Marketplace Vendor Strategy, at Pax8 said:  “We’re delighted to welcome EasyDMARC to the Pax8 Marketplace as an enterprise-class DMARC solution provider. This integration gives MSPs the tools they need to meet the growing demand for email security, with simplified deployment, billing, and bundling benefits. With EasyDMARC’s technical capabilities and intelligence, MSPs can deliver robust protection against phishing threats without the technical hassle that often holds businesses back.” About EasyDMARC EasyDMARC is a cloud-native B2B SaaS solution that addresses email security and deliverability problems with just a few clicks. For Managed Service Providers seeking to increase their revenue, EasyDMARC presents an ideal solution. The email authentication platform streamlines domain management, providing capabilities such as organizational control, domain grouping, and access management. Additionally, EasyDMARC offers a comprehensive sales and marketing enablement program designed to boost DMARC sales. All of these features are available for MSPs on a scalable platform with a flexible pay-as-you-go pricing model. For more information on the EasyDMARC, visit: / About Pax8  Pax8 is the technology marketplace of the future, linking partners, vendors, and small to midsized businessesthrough AI-powered insights and comprehensive product support. With a global partner ecosystem of over 38,000 managed service providers, Pax8 empowers SMBs worldwide by providing software and services that unlock their growth potential and enhance their security. Committed to innovating cloud commerce at scale, Pax8 drives customer acquisition and solution consumption across its entire ecosystem. Find out more: / The post EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs appeared first on EasyDMARC. #easydmarc #integrates #with #pax8 #marketplace
    EASYDMARC.COM
    EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs
    Originally published at EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs by Anush Yolyan. The integration will deliver simple, accessible, and streamlined email security for vulnerable inboxes Global, 4 November 2024 – US-based email security firm EasyDMARC has today announced its integration with Pax8 Marketplace, the leading cloud commerce marketplace. As one of the first DMARC solution providers on the Pax8 Marketplace, EasyDMARC is expanding its mission to protect inboxes from the rising threat of phishing attacks with a rigorous, user-friendly DMARC solution. The integration comes as Google highlights the impressive results of recently implemented email authentication measures for bulk senders: a 65% reduction in unauthenticated messages to Gmail users, a 50% increase in bulk senders following best security practices, and 265 billion fewer unauthenticated messages sent in 2024. With email being such a crucial communication channel for businesses, email authentication measures are an essential part of any business’s cybersecurity offering.  Key features of the integration include: Centralized billing With centralized billing, customers can now streamline their cloud services under a single pane of glass, simplifying the management and billing of their EasyDMARC solution. This consolidated approach enables partners to reduce administrative complexity and manage all cloud expenses through one interface, providing a seamless billing and support experience. Automated provisioning  Through automated provisioning, Pax8’s automation capabilities make deploying DMARC across client accounts quick and hassle-free. By eliminating manual configurations, this integration ensures that customers can implement email security solutions rapidly, allowing them to safeguard client inboxes without delay. Bundled offerings The bundled offerings available through Pax8 allow partners to enhance their service portfolios by combining EasyDMARC with complementary security solutions. By creating all-in-one security packages, partners can offer their clients more robust protection, addressing a broader range of security needs from a single, trusted platform. Gerasim Hovhannisyan, Co-Founder and CEO of EasyDMARC, said: “We’re thrilled to be working with Pax8  to provide MSPs with a streamlined, effective way to deliver top-tier email security to their clients, all within a platform that equips them with everything needed to stay secure.  As phishing attacks grow in frequency and sophistication, businesses can no longer afford to overlook the importance of email security. Email authentication is a vital defense against the evolving threat of phishing and is crucial in preserving the integrity of email communication. This integration is designed to allow businesses of all sizes to benefit from DMARC’s extensive capabilities.” Ryan Burton, Vice President of Marketplace Vendor Strategy, at Pax8 said:  “We’re delighted to welcome EasyDMARC to the Pax8 Marketplace as an enterprise-class DMARC solution provider. This integration gives MSPs the tools they need to meet the growing demand for email security, with simplified deployment, billing, and bundling benefits. With EasyDMARC’s technical capabilities and intelligence, MSPs can deliver robust protection against phishing threats without the technical hassle that often holds businesses back.” About EasyDMARC EasyDMARC is a cloud-native B2B SaaS solution that addresses email security and deliverability problems with just a few clicks. For Managed Service Providers seeking to increase their revenue, EasyDMARC presents an ideal solution. The email authentication platform streamlines domain management, providing capabilities such as organizational control, domain grouping, and access management. Additionally, EasyDMARC offers a comprehensive sales and marketing enablement program designed to boost DMARC sales. All of these features are available for MSPs on a scalable platform with a flexible pay-as-you-go pricing model. For more information on the EasyDMARC, visit: https://easydmarc.com/ About Pax8  Pax8 is the technology marketplace of the future, linking partners, vendors, and small to midsized businesses (SMBs) through AI-powered insights and comprehensive product support. With a global partner ecosystem of over 38,000 managed service providers, Pax8 empowers SMBs worldwide by providing software and services that unlock their growth potential and enhance their security. Committed to innovating cloud commerce at scale, Pax8 drives customer acquisition and solution consumption across its entire ecosystem. Find out more: https://www.pax8.com/en-us/ The post EasyDMARC Integrates With Pax8 Marketplace To Simplify Email Security For MSPs appeared first on EasyDMARC.
    0 Comentários 0 Compartilhamentos
  • How to Implement Insertion Sort in Java: Step-by-Step Guide

    Posted on : June 13, 2025

    By

    Tech World Times

    Uncategorized 

    Rate this post

    Sorting is important in programming. It helps organize data. Sorting improves performance in searching, analysis, and reporting. There are many sorting algorithms. One of the simplest is Insertion Sort.
    In this article, we will learn how to implement Insertion Sort in Java. We will explain each step in simple words. You will see examples and understand how it works.
    What Is Insertion Sort?
    Insertion Sort is a simple sorting algorithm. It works like how you sort playing cards. You take one card at a time and place it in the right position. It compares the current element with those before it. If needed, it shifts elements to the right. Then, it inserts the current element at the correct place.
    How Insertion Sort Works
    Let’s understand with a small list:
    Example List:Steps:

    First elementis already sorted.
    Compare 3 with 8. Move 8 right. Insert 3 before it →Compare 5 with 8. Move 8 right. Insert 5 after 3 →Compare 1 with 8, 5, 3. Move them right. Insert 1 at start →Now the list is sorted!
    Why Use Insertion Sort?
    Insertion Sort is simple and easy to code. It works well for:

    Small datasets
    Nearly sorted lists
    Educational purposes and practice

    However, it is not good for large datasets. It has a time complexity of O.
    Time Complexity of Insertion Sort

    Best Case: OAverage Case: OWorst Case: OIt performs fewer steps in nearly sorted data.
    How to Implement Insertion Sort in Java
    Now let’s write the code for Insertion Sort in Java. We will explain each part.
    Step 1: Define a Class
    javaCopyEditpublic class InsertionSortExample {
    // Code goes here
    }

    We create a class named InsertionSortExample.
    Step 2: Create the Sorting Method
    javaCopyEditpublic static void insertionSort{
    int n = arr.length;
    for{
    int key = arr;
    int j = i - 1;

    while{
    arr= arr;
    j = j - 1;
    }
    arr= key;
    }
    }

    Let’s break it down:

    arris the current value.
    j starts from the previous index.
    While arr> key, shift arrto the right.
    Insert the key at the correct position.

    This logic sorts the array step by step.
    Step 3: Create the Main Method
    Now we test the code.
    javaCopyEditpublic static void main{
    intnumbers = {9, 5, 1, 4, 3};

    System.out.println;
    printArray;

    insertionSort;

    System.out.println;
    printArray;
    }

    This method:

    Creates an array of numbers
    Prints the array before sorting
    Calls the sort method
    Prints the array after sorting

    Step 4: Print the Array
    Let’s add a helper method to print the array.
    javaCopyEditpublic static void printArray{
    for{
    System.out.print;
    }
    System.out.println;
    }

    Now you can see how the array changes before and after sorting.
    Full Code Example
    javaCopyEditpublic class InsertionSortExample {

    public static void insertionSort{
    int n = arr.length;
    for{
    int key = arr;
    int j = i - 1;

    while{
    arr= arr;
    j = j - 1;
    }
    arr= key;
    }
    }

    public static void printArray{
    for{
    System.out.print;
    }
    System.out.println;
    }

    public static void main{
    intnumbers = {9, 5, 1, 4, 3};

    System.out.println;
    printArray;

    insertionSort;

    System.out.println;
    printArray;
    }
    }

    Sample Output
    yamlCopyEditBefore sorting:
    9 5 1 4 3
    After sorting:
    1 3 4 5 9

    This confirms that the sorting works correctly.
    Advantages of Insertion Sort in Java

    Easy to implement
    Works well with small inputs
    Stable sortGood for educational use

    When Not to Use Insertion Sort
    Avoid Insertion Sort when:

    The dataset is large
    Performance is critical
    Better algorithms like Merge Sort or Quick Sort are available

    Real-World Uses

    Sorting small records in a database
    Teaching algorithm basics
    Handling partially sorted arrays

    Even though it is not the fastest, it is useful in many simple tasks.
    Final Tips

    Practice with different inputs
    Add print statements to see how it works
    Try sorting strings or objects
    Use Java’s built-in sort methods for large arrays

    Conclusion
    Insertion Sort in Java is a great way to learn sorting. It is simple and easy to understand. In this guide, we showed how to implement it step-by-step. We covered the logic, code, and output. We also explained when to use it. Now you can try it yourself. Understanding sorting helps in coding interviews and software development. Keep practicing and exploring other sorting methods too. The more you practice, the better you understand algorithms.
    Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
    #how #implement #insertion #sort #java
    How to Implement Insertion Sort in Java: Step-by-Step Guide
    Posted on : June 13, 2025 By Tech World Times Uncategorized  Rate this post Sorting is important in programming. It helps organize data. Sorting improves performance in searching, analysis, and reporting. There are many sorting algorithms. One of the simplest is Insertion Sort. In this article, we will learn how to implement Insertion Sort in Java. We will explain each step in simple words. You will see examples and understand how it works. What Is Insertion Sort? Insertion Sort is a simple sorting algorithm. It works like how you sort playing cards. You take one card at a time and place it in the right position. It compares the current element with those before it. If needed, it shifts elements to the right. Then, it inserts the current element at the correct place. How Insertion Sort Works Let’s understand with a small list: Example List:Steps: First elementis already sorted. Compare 3 with 8. Move 8 right. Insert 3 before it →Compare 5 with 8. Move 8 right. Insert 5 after 3 →Compare 1 with 8, 5, 3. Move them right. Insert 1 at start →Now the list is sorted! Why Use Insertion Sort? Insertion Sort is simple and easy to code. It works well for: Small datasets Nearly sorted lists Educational purposes and practice However, it is not good for large datasets. It has a time complexity of O. Time Complexity of Insertion Sort Best Case: OAverage Case: OWorst Case: OIt performs fewer steps in nearly sorted data. How to Implement Insertion Sort in Java Now let’s write the code for Insertion Sort in Java. We will explain each part. Step 1: Define a Class javaCopyEditpublic class InsertionSortExample { // Code goes here } We create a class named InsertionSortExample. Step 2: Create the Sorting Method javaCopyEditpublic static void insertionSort{ int n = arr.length; for{ int key = arr; int j = i - 1; while{ arr= arr; j = j - 1; } arr= key; } } Let’s break it down: arris the current value. j starts from the previous index. While arr> key, shift arrto the right. Insert the key at the correct position. This logic sorts the array step by step. Step 3: Create the Main Method Now we test the code. javaCopyEditpublic static void main{ intnumbers = {9, 5, 1, 4, 3}; System.out.println; printArray; insertionSort; System.out.println; printArray; } This method: Creates an array of numbers Prints the array before sorting Calls the sort method Prints the array after sorting Step 4: Print the Array Let’s add a helper method to print the array. javaCopyEditpublic static void printArray{ for{ System.out.print; } System.out.println; } Now you can see how the array changes before and after sorting. Full Code Example javaCopyEditpublic class InsertionSortExample { public static void insertionSort{ int n = arr.length; for{ int key = arr; int j = i - 1; while{ arr= arr; j = j - 1; } arr= key; } } public static void printArray{ for{ System.out.print; } System.out.println; } public static void main{ intnumbers = {9, 5, 1, 4, 3}; System.out.println; printArray; insertionSort; System.out.println; printArray; } } Sample Output yamlCopyEditBefore sorting: 9 5 1 4 3 After sorting: 1 3 4 5 9 This confirms that the sorting works correctly. Advantages of Insertion Sort in Java Easy to implement Works well with small inputs Stable sortGood for educational use When Not to Use Insertion Sort Avoid Insertion Sort when: The dataset is large Performance is critical Better algorithms like Merge Sort or Quick Sort are available Real-World Uses Sorting small records in a database Teaching algorithm basics Handling partially sorted arrays Even though it is not the fastest, it is useful in many simple tasks. Final Tips Practice with different inputs Add print statements to see how it works Try sorting strings or objects Use Java’s built-in sort methods for large arrays Conclusion Insertion Sort in Java is a great way to learn sorting. It is simple and easy to understand. In this guide, we showed how to implement it step-by-step. We covered the logic, code, and output. We also explained when to use it. Now you can try it yourself. Understanding sorting helps in coding interviews and software development. Keep practicing and exploring other sorting methods too. The more you practice, the better you understand algorithms. Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com #how #implement #insertion #sort #java
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    How to Implement Insertion Sort in Java: Step-by-Step Guide
    Posted on : June 13, 2025 By Tech World Times Uncategorized  Rate this post Sorting is important in programming. It helps organize data. Sorting improves performance in searching, analysis, and reporting. There are many sorting algorithms. One of the simplest is Insertion Sort. In this article, we will learn how to implement Insertion Sort in Java. We will explain each step in simple words. You will see examples and understand how it works. What Is Insertion Sort? Insertion Sort is a simple sorting algorithm. It works like how you sort playing cards. You take one card at a time and place it in the right position. It compares the current element with those before it. If needed, it shifts elements to the right. Then, it inserts the current element at the correct place. How Insertion Sort Works Let’s understand with a small list: Example List: [8, 3, 5, 1] Steps: First element (8) is already sorted. Compare 3 with 8. Move 8 right. Insert 3 before it → [3, 8, 5, 1] Compare 5 with 8. Move 8 right. Insert 5 after 3 → [3, 5, 8, 1] Compare 1 with 8, 5, 3. Move them right. Insert 1 at start → [1, 3, 5, 8] Now the list is sorted! Why Use Insertion Sort? Insertion Sort is simple and easy to code. It works well for: Small datasets Nearly sorted lists Educational purposes and practice However, it is not good for large datasets. It has a time complexity of O(n²). Time Complexity of Insertion Sort Best Case (already sorted): O(n) Average Case: O(n²) Worst Case (reversed list): O(n²) It performs fewer steps in nearly sorted data. How to Implement Insertion Sort in Java Now let’s write the code for Insertion Sort in Java. We will explain each part. Step 1: Define a Class javaCopyEditpublic class InsertionSortExample { // Code goes here } We create a class named InsertionSortExample. Step 2: Create the Sorting Method javaCopyEditpublic static void insertionSort(int[] arr) { int n = arr.length; for (int i = 1; i < n; i++) { int key = arr[i]; int j = i - 1; while (j >= 0 && arr[j] > key) { arr[j + 1] = arr[j]; j = j - 1; } arr[j + 1] = key; } } Let’s break it down: arr[i] is the current value (called key). j starts from the previous index. While arr[j] > key, shift arr[j] to the right. Insert the key at the correct position. This logic sorts the array step by step. Step 3: Create the Main Method Now we test the code. javaCopyEditpublic static void main(String[] args) { int[] numbers = {9, 5, 1, 4, 3}; System.out.println("Before sorting:"); printArray(numbers); insertionSort(numbers); System.out.println("After sorting:"); printArray(numbers); } This method: Creates an array of numbers Prints the array before sorting Calls the sort method Prints the array after sorting Step 4: Print the Array Let’s add a helper method to print the array. javaCopyEditpublic static void printArray(int[] arr) { for (int number : arr) { System.out.print(number + " "); } System.out.println(); } Now you can see how the array changes before and after sorting. Full Code Example javaCopyEditpublic class InsertionSortExample { public static void insertionSort(int[] arr) { int n = arr.length; for (int i = 1; i < n; i++) { int key = arr[i]; int j = i - 1; while (j >= 0 && arr[j] > key) { arr[j + 1] = arr[j]; j = j - 1; } arr[j + 1] = key; } } public static void printArray(int[] arr) { for (int number : arr) { System.out.print(number + " "); } System.out.println(); } public static void main(String[] args) { int[] numbers = {9, 5, 1, 4, 3}; System.out.println("Before sorting:"); printArray(numbers); insertionSort(numbers); System.out.println("After sorting:"); printArray(numbers); } } Sample Output yamlCopyEditBefore sorting: 9 5 1 4 3 After sorting: 1 3 4 5 9 This confirms that the sorting works correctly. Advantages of Insertion Sort in Java Easy to implement Works well with small inputs Stable sort (keeps equal items in order) Good for educational use When Not to Use Insertion Sort Avoid Insertion Sort when: The dataset is large Performance is critical Better algorithms like Merge Sort or Quick Sort are available Real-World Uses Sorting small records in a database Teaching algorithm basics Handling partially sorted arrays Even though it is not the fastest, it is useful in many simple tasks. Final Tips Practice with different inputs Add print statements to see how it works Try sorting strings or objects Use Java’s built-in sort methods for large arrays Conclusion Insertion Sort in Java is a great way to learn sorting. It is simple and easy to understand. In this guide, we showed how to implement it step-by-step. We covered the logic, code, and output. We also explained when to use it. Now you can try it yourself. Understanding sorting helps in coding interviews and software development. Keep practicing and exploring other sorting methods too. The more you practice, the better you understand algorithms. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
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  • Selection Sort Time Complexity: Best, Worst, and Average Cases

    Development and Testing 

    Rate this post

    Sorting is a basic task in programming. It arranges data in order. There are many sorting algorithms. Selection Sort is one of the simplest sorting methods. It is easy to understand and code. But it is not the fastest. In this guide, we will explain the Selection Sort Time Complexity. We will cover best, worst, and average cases.
    What Is Selection Sort?
    Selection Sort works by selecting the smallest element from the list. It places it in the correct position. It repeats this process for all elements. One by one, it moves the smallest values to the front.
    Let’s see an example:
    Input:Step 1: Smallest is 2 → swap with 5 →Step 2: Smallest in remaining is 3 → already correctStep 3: Smallest in remaining is 5 → swap with 8 →Now the list is sorted.How Selection Sort Works
    Selection Sort uses two loops. The outer loop moves one index at a time. The inner loop finds the smallest element. After each pass, the smallest value is moved to the front. The position is fixed. Selection Sort does not care if the list is sorted or not. It always does the same steps.
    Selection Sort Algorithm
    Here is the basic algorithm:

    Start from the first element
    Find the smallest in the rest of the list
    Swap it with the current element
    Repeat for each element

    This repeats until all elements are sorted.
    Selection Sort CodejavaCopyEditpublic class SelectionSort {
    public static void sort{
    int n = arr.length;
    for{
    int min = i;
    for{
    if{
    min = j;
    }
    }
    int temp = arr;
    arr= arr;
    arr= temp;
    }
    }
    }

    This code uses two loops. The outer loop runs n-1 times. The inner loop finds the minimum.
    Selection Sort Time Complexity
    Now let’s understand the main topic. Let’s analyze Selection Sort Time Complexity in three cases.
    1. Best Case
    Even if the array is already sorted, Selection Sort checks all elements. It keeps comparing and swapping.

    Time Complexity: OReason: Inner loop runs fully, regardless of the order
    Example Input:Even here, every comparison still happens. Only fewer swaps occur, but comparisons remain the same.
    2. Worst Case
    This happens when the array is in reverse order. But Selection Sort does not optimize for this.

    Time Complexity: OReason: Still needs full comparisons
    Example Input:Even in reverse, the steps are the same. It compares and finds the smallest element every time.
    3. Average Case
    This is when elements are randomly placed. It is the most common scenario in real-world problems.

    Time Complexity: OReason: Still compares each element in the inner loop
    Example Input:Selection Sort does not change behavior based on input order. So the complexity remains the same.
    Why Is It Always O?
    Selection Sort compares all pairs of elements. The number of comparisons does not change.
    Total comparisons = n ×/ 2
    That’s why the time complexity is always O.It does not reduce steps in any case. It does not take advantage of sorted elements.
    Space Complexity
    Selection Sort does not need extra space. It sorts in place.

    Space Complexity: OOnly a few variables are used
    No extra arrays or memory needed

    This is one good point of the Selection Sort.
    Comparison with Other Algorithms
    Let’s compare Selection Sort with other basic sorts:
    AlgorithmBest CaseAverage CaseWorst CaseSpaceSelection SortOOOOBubble SortOOOOInsertion SortOOOOMerge SortOOOOQuick SortOOOOAs you see, Selection Sort is slower than Merge Sort and Quick Sort.
    Advantages of Selection Sort

    Very simple and easy to understand
    Works well with small datasets
    Needs very little memory
    Good for learning purposes

    Disadvantages of Selection Sort

    Slow on large datasets
    Always takes the same time, even if sorted
    Not efficient for real-world use

    When to Use Selection Sort
    Use Selection Sort when:

    You are working with a very small dataset
    You want to teach or learn sorting logic
    You want stable, low-memory sorting

    Avoid it for:

    Large datasets
    Performance-sensitive programs

    Conclusion
    Selection Sort Time Complexity is simple to understand. But it is not efficient for big problems. It always takes Otime, no matter the case. That is the same for best, worst, and average inputs. Still, it is useful in some cases. It’s great for learning sorting basics. It uses very little memory. If you’re working with small arrays, Selection Sort is fine. For large data, use better algorithms. Understanding its time complexity helps you choose the right algorithm. Always pick the tool that fits your task.
    Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
    #selection #sort #time #complexity #best
    Selection Sort Time Complexity: Best, Worst, and Average Cases
    Development and Testing  Rate this post Sorting is a basic task in programming. It arranges data in order. There are many sorting algorithms. Selection Sort is one of the simplest sorting methods. It is easy to understand and code. But it is not the fastest. In this guide, we will explain the Selection Sort Time Complexity. We will cover best, worst, and average cases. What Is Selection Sort? Selection Sort works by selecting the smallest element from the list. It places it in the correct position. It repeats this process for all elements. One by one, it moves the smallest values to the front. Let’s see an example: Input:Step 1: Smallest is 2 → swap with 5 →Step 2: Smallest in remaining is 3 → already correctStep 3: Smallest in remaining is 5 → swap with 8 →Now the list is sorted.How Selection Sort Works Selection Sort uses two loops. The outer loop moves one index at a time. The inner loop finds the smallest element. After each pass, the smallest value is moved to the front. The position is fixed. Selection Sort does not care if the list is sorted or not. It always does the same steps. Selection Sort Algorithm Here is the basic algorithm: Start from the first element Find the smallest in the rest of the list Swap it with the current element Repeat for each element This repeats until all elements are sorted. Selection Sort CodejavaCopyEditpublic class SelectionSort { public static void sort{ int n = arr.length; for{ int min = i; for{ if{ min = j; } } int temp = arr; arr= arr; arr= temp; } } } This code uses two loops. The outer loop runs n-1 times. The inner loop finds the minimum. Selection Sort Time Complexity Now let’s understand the main topic. Let’s analyze Selection Sort Time Complexity in three cases. 1. Best Case Even if the array is already sorted, Selection Sort checks all elements. It keeps comparing and swapping. Time Complexity: OReason: Inner loop runs fully, regardless of the order Example Input:Even here, every comparison still happens. Only fewer swaps occur, but comparisons remain the same. 2. Worst Case This happens when the array is in reverse order. But Selection Sort does not optimize for this. Time Complexity: OReason: Still needs full comparisons Example Input:Even in reverse, the steps are the same. It compares and finds the smallest element every time. 3. Average Case This is when elements are randomly placed. It is the most common scenario in real-world problems. Time Complexity: OReason: Still compares each element in the inner loop Example Input:Selection Sort does not change behavior based on input order. So the complexity remains the same. Why Is It Always O? Selection Sort compares all pairs of elements. The number of comparisons does not change. Total comparisons = n ×/ 2 That’s why the time complexity is always O.It does not reduce steps in any case. It does not take advantage of sorted elements. Space Complexity Selection Sort does not need extra space. It sorts in place. Space Complexity: OOnly a few variables are used No extra arrays or memory needed This is one good point of the Selection Sort. Comparison with Other Algorithms Let’s compare Selection Sort with other basic sorts: AlgorithmBest CaseAverage CaseWorst CaseSpaceSelection SortOOOOBubble SortOOOOInsertion SortOOOOMerge SortOOOOQuick SortOOOOAs you see, Selection Sort is slower than Merge Sort and Quick Sort. Advantages of Selection Sort Very simple and easy to understand Works well with small datasets Needs very little memory Good for learning purposes Disadvantages of Selection Sort Slow on large datasets Always takes the same time, even if sorted Not efficient for real-world use When to Use Selection Sort Use Selection Sort when: You are working with a very small dataset You want to teach or learn sorting logic You want stable, low-memory sorting Avoid it for: Large datasets Performance-sensitive programs Conclusion Selection Sort Time Complexity is simple to understand. But it is not efficient for big problems. It always takes Otime, no matter the case. That is the same for best, worst, and average inputs. Still, it is useful in some cases. It’s great for learning sorting basics. It uses very little memory. If you’re working with small arrays, Selection Sort is fine. For large data, use better algorithms. Understanding its time complexity helps you choose the right algorithm. Always pick the tool that fits your task. Tech World TimesTech World Times, a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com #selection #sort #time #complexity #best
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    Selection Sort Time Complexity: Best, Worst, and Average Cases
    Development and Testing  Rate this post Sorting is a basic task in programming. It arranges data in order. There are many sorting algorithms. Selection Sort is one of the simplest sorting methods. It is easy to understand and code. But it is not the fastest. In this guide, we will explain the Selection Sort Time Complexity. We will cover best, worst, and average cases. What Is Selection Sort? Selection Sort works by selecting the smallest element from the list. It places it in the correct position. It repeats this process for all elements. One by one, it moves the smallest values to the front. Let’s see an example: Input: [5, 3, 8, 2]Step 1: Smallest is 2 → swap with 5 → [2, 3, 8, 5]Step 2: Smallest in remaining is 3 → already correctStep 3: Smallest in remaining is 5 → swap with 8 → [2, 3, 5, 8] Now the list is sorted.How Selection Sort Works Selection Sort uses two loops. The outer loop moves one index at a time. The inner loop finds the smallest element. After each pass, the smallest value is moved to the front. The position is fixed. Selection Sort does not care if the list is sorted or not. It always does the same steps. Selection Sort Algorithm Here is the basic algorithm: Start from the first element Find the smallest in the rest of the list Swap it with the current element Repeat for each element This repeats until all elements are sorted. Selection Sort Code (Java Example) javaCopyEditpublic class SelectionSort { public static void sort(int[] arr) { int n = arr.length; for (int i = 0; i < n - 1; i++) { int min = i; for (int j = i + 1; j < n; j++) { if (arr[j] < arr[min]) { min = j; } } int temp = arr[min]; arr[min] = arr[i]; arr[i] = temp; } } } This code uses two loops. The outer loop runs n-1 times. The inner loop finds the minimum. Selection Sort Time Complexity Now let’s understand the main topic. Let’s analyze Selection Sort Time Complexity in three cases. 1. Best Case Even if the array is already sorted, Selection Sort checks all elements. It keeps comparing and swapping. Time Complexity: O(n²) Reason: Inner loop runs fully, regardless of the order Example Input: [1, 2, 3, 4, 5] Even here, every comparison still happens. Only fewer swaps occur, but comparisons remain the same. 2. Worst Case This happens when the array is in reverse order. But Selection Sort does not optimize for this. Time Complexity: O(n²) Reason: Still needs full comparisons Example Input: [5, 4, 3, 2, 1] Even in reverse, the steps are the same. It compares and finds the smallest element every time. 3. Average Case This is when elements are randomly placed. It is the most common scenario in real-world problems. Time Complexity: O(n²) Reason: Still compares each element in the inner loop Example Input: [3, 1, 4, 2, 5] Selection Sort does not change behavior based on input order. So the complexity remains the same. Why Is It Always O(n²)? Selection Sort compares all pairs of elements. The number of comparisons does not change. Total comparisons = n × (n – 1) / 2 That’s why the time complexity is always O(n²).It does not reduce steps in any case. It does not take advantage of sorted elements. Space Complexity Selection Sort does not need extra space. It sorts in place. Space Complexity: O(1) Only a few variables are used No extra arrays or memory needed This is one good point of the Selection Sort. Comparison with Other Algorithms Let’s compare Selection Sort with other basic sorts: AlgorithmBest CaseAverage CaseWorst CaseSpaceSelection SortO(n²)O(n²)O(n²)O(1)Bubble SortO(n)O(n²)O(n²)O(1)Insertion SortO(n)O(n²)O(n²)O(1)Merge SortO(n log n)O(n log n)O(n log n)O(n)Quick SortO(n log n)O(n log n)O(n²)O(log n) As you see, Selection Sort is slower than Merge Sort and Quick Sort. Advantages of Selection Sort Very simple and easy to understand Works well with small datasets Needs very little memory Good for learning purposes Disadvantages of Selection Sort Slow on large datasets Always takes the same time, even if sorted Not efficient for real-world use When to Use Selection Sort Use Selection Sort when: You are working with a very small dataset You want to teach or learn sorting logic You want stable, low-memory sorting Avoid it for: Large datasets Performance-sensitive programs Conclusion Selection Sort Time Complexity is simple to understand. But it is not efficient for big problems. It always takes O(n²) time, no matter the case. That is the same for best, worst, and average inputs. Still, it is useful in some cases. It’s great for learning sorting basics. It uses very little memory. If you’re working with small arrays, Selection Sort is fine. For large data, use better algorithms. Understanding its time complexity helps you choose the right algorithm. Always pick the tool that fits your task. Tech World TimesTech World Times (TWT), a global collective focusing on the latest tech news and trends in blockchain, Fintech, Development & Testing, AI and Startups. If you are looking for the guest post then contact at techworldtimes@gmail.com
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  • Watch Out for Malicious Unsubscribe Links

    In addition to the flood of spam texts you receive on a daily basis, your email inbox is likely filled with newsletters, promotions, and other messages that you don't care to read and perhaps don't know why you receive. But you shouldn't just start clicking unsubscribe links, which may open you up to certain cybersecurity risks. Email unsubscribe links may be maliciousWhile email unsubscribe links may seem innocuous, especially if you generally trust the sender, security experts say there are a number of ways in which threat actors can leverage these links for malicious purposes. Like responding to a spam text or answering a spam call, clicking "unsubscribe" confirms that your email address is active, giving cyber criminals an incentive to keep targeting you.In some cases, unsubscribe links can be hijacked to send users to phishing websites, where you are asked to enter your login credentials to complete the process. According to the folks at DNSFilter, one in every 644 clicks of email unsubscribe links can land you on a malicious website. While you do have to confirm your email address in some legitimate cases, you shouldn't enter a password, which is likely a scam. Bottom line: If you don't trust the sender, you certainly shouldn't trust any links contained within the email. How to safely unsubscribe from emails Even if unsubscribe links are safe, it's a pain to go through the multi-step process of clicking through individual emails and opening new browser windows to confirm. To minimize hassle and avoid the risk of malicious links in individual emails, you can use unsubscribe features built into your email client, which are less likely to be compromised by threat actors because they aren't tied to the email itself. In Gmail, tap More > Manage subscriptions in your left-hand navigation barand scroll to the sender. Click Unsubscribe to the right of the number of emails sent recently. You can also unsubscribe from individual emails by opening the message and clicking Unsubscribe next to the sender's name. In some cases, you may be directed to the sender's website to complete the process.You can also mark the message as spam or block the sender. In Outlook, go to Settings > Mail > Subscriptions > Your current subscriptions and select Unsubscribe, then tap OK. Alternatively, you can block the sender by clicking the three dots and selecting Block > OK. Alternatively, you can filter unwanted emails to a different folder, so while you'll still receive them, they won't clog up your main inbox. In Gmail, open the message then click More > Filter messages like these to set up filter criteria, whether that's sending to another folder, deleting it, or marking it as spam. You can create similar rules in Outlook by right-clicking the message in your message list and going to Rules > Create rule. A final option is to use a disposable email alias to subscribe to newsletters and promotional emails or when signing up for accounts, which makes it easy to filter messages or delete the address entirely without affecting your main inbox.
    #watch #out #malicious #unsubscribe #links
    Watch Out for Malicious Unsubscribe Links
    In addition to the flood of spam texts you receive on a daily basis, your email inbox is likely filled with newsletters, promotions, and other messages that you don't care to read and perhaps don't know why you receive. But you shouldn't just start clicking unsubscribe links, which may open you up to certain cybersecurity risks. Email unsubscribe links may be maliciousWhile email unsubscribe links may seem innocuous, especially if you generally trust the sender, security experts say there are a number of ways in which threat actors can leverage these links for malicious purposes. Like responding to a spam text or answering a spam call, clicking "unsubscribe" confirms that your email address is active, giving cyber criminals an incentive to keep targeting you.In some cases, unsubscribe links can be hijacked to send users to phishing websites, where you are asked to enter your login credentials to complete the process. According to the folks at DNSFilter, one in every 644 clicks of email unsubscribe links can land you on a malicious website. While you do have to confirm your email address in some legitimate cases, you shouldn't enter a password, which is likely a scam. Bottom line: If you don't trust the sender, you certainly shouldn't trust any links contained within the email. How to safely unsubscribe from emails Even if unsubscribe links are safe, it's a pain to go through the multi-step process of clicking through individual emails and opening new browser windows to confirm. To minimize hassle and avoid the risk of malicious links in individual emails, you can use unsubscribe features built into your email client, which are less likely to be compromised by threat actors because they aren't tied to the email itself. In Gmail, tap More > Manage subscriptions in your left-hand navigation barand scroll to the sender. Click Unsubscribe to the right of the number of emails sent recently. You can also unsubscribe from individual emails by opening the message and clicking Unsubscribe next to the sender's name. In some cases, you may be directed to the sender's website to complete the process.You can also mark the message as spam or block the sender. In Outlook, go to Settings > Mail > Subscriptions > Your current subscriptions and select Unsubscribe, then tap OK. Alternatively, you can block the sender by clicking the three dots and selecting Block > OK. Alternatively, you can filter unwanted emails to a different folder, so while you'll still receive them, they won't clog up your main inbox. In Gmail, open the message then click More > Filter messages like these to set up filter criteria, whether that's sending to another folder, deleting it, or marking it as spam. You can create similar rules in Outlook by right-clicking the message in your message list and going to Rules > Create rule. A final option is to use a disposable email alias to subscribe to newsletters and promotional emails or when signing up for accounts, which makes it easy to filter messages or delete the address entirely without affecting your main inbox. #watch #out #malicious #unsubscribe #links
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    Watch Out for Malicious Unsubscribe Links
    In addition to the flood of spam texts you receive on a daily basis, your email inbox is likely filled with newsletters, promotions, and other messages that you don't care to read and perhaps don't know why you receive. But you shouldn't just start clicking unsubscribe links, which may open you up to certain cybersecurity risks. Email unsubscribe links may be maliciousWhile email unsubscribe links may seem innocuous, especially if you generally trust the sender, security experts say there are a number of ways in which threat actors can leverage these links for malicious purposes. Like responding to a spam text or answering a spam call, clicking "unsubscribe" confirms that your email address is active, giving cyber criminals an incentive to keep targeting you.In some cases, unsubscribe links can be hijacked to send users to phishing websites, where you are asked to enter your login credentials to complete the process. According to the folks at DNSFilter, one in every 644 clicks of email unsubscribe links can land you on a malicious website. While you do have to confirm your email address in some legitimate cases, you shouldn't enter a password, which is likely a scam. Bottom line: If you don't trust the sender, you certainly shouldn't trust any links contained within the email. How to safely unsubscribe from emails Even if unsubscribe links are safe, it's a pain to go through the multi-step process of clicking through individual emails and opening new browser windows to confirm. To minimize hassle and avoid the risk of malicious links in individual emails, you can use unsubscribe features built into your email client, which are less likely to be compromised by threat actors because they aren't tied to the email itself. In Gmail, tap More > Manage subscriptions in your left-hand navigation bar (Menu > Manage subscriptions on mobile) and scroll to the sender. Click Unsubscribe to the right of the number of emails sent recently. You can also unsubscribe from individual emails by opening the message and clicking Unsubscribe next to the sender's name. In some cases, you may be directed to the sender's website to complete the process. (Note that Gmail may not consider all email campaigns eligible for one-click unsubscribe.) You can also mark the message as spam or block the sender. In Outlook, go to Settings > Mail > Subscriptions > Your current subscriptions and select Unsubscribe, then tap OK. Alternatively, you can block the sender by clicking the three dots and selecting Block > OK. Alternatively, you can filter unwanted emails to a different folder (including spam), so while you'll still receive them, they won't clog up your main inbox. In Gmail, open the message then click More > Filter messages like these to set up filter criteria, whether that's sending to another folder, deleting it, or marking it as spam. You can create similar rules in Outlook by right-clicking the message in your message list and going to Rules > Create rule. A final option is to use a disposable email alias to subscribe to newsletters and promotional emails or when signing up for accounts, which makes it easy to filter messages or delete the address entirely without affecting your main inbox.
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