{"componentChunkName":"component---src-templates-blog-post-jsx","path":"/blogs/selectionSort","result":{"data":{"blog":{"frontmatter":{"title":"SELECTION SORT","thumbnail":"blog59","date":"April 26, 2021","dsaCppCodeFile":"https://drive.google.com/file/d/1M8yNCsm99h0en0-b5FSo8hYayMNbZpVE/view?usp=sharing"},"excerpt":"
\n

Introduction

\n
\n

\n Selection sort is an in-place sorting algorithm. In every\n iteration, we find the minimum value and swap it with the\n current index. That is to say that we start looping with index\n i and loop again from i+1 till the end, find the min value and\n swap it with the element at index i.\n

\n

\n This algorithm falls under Brute Force Technique which is a\n straight forward approach to solve a problem. Let's look at\n the working of this algorithm.\n

\n
\n
\n
\n

Working Procedure

\n

\n Do refer the code available the end of this section to\n understand the following theory.\n

\n
    \n
  1. Consider an array of n elements.
    2. \n
  2. Loop the array from i = 0 to n-2(Outer loop).
    3. \n
  3. Assign min = i.
    4. \n
  4. Loop the array from j = 0 to n-i-1(Inner loop).
    5. \n
  5. Assign min = j if a[j] < a[min].
    6. \n
  6. \n After the inner loop ends, if min != i then swap a[i] &\n a[min]. (It means that if we found the index of minimum value\n among the elements i+1 to n-1 then swap it with the current\n element i.e i).\n
    7. \n
  7. \n After the outer loop ends, we get the required sorted array.\n
    8. \n
\n
\n
\n

Time Complexity

\n
\n

\n PS: We give random inputs because the no. of input will\n generally be 100 or 1000 to find the time complexity and\n manually giving so many inputs is cumbersome work.\n

\n

\n The basic operation in this algorithm is the comparision\n between current element and the next element(step 5 in the\n above working procedure). So increment the count variable\n above this if condition to get the count of no. of times the\n basic operation has been performed.\n

\n \n \n \"Selection\n \n

\n Time Complexity: O(n2)\n

\n
\n
\n Similar posts:\n Bubble Sort\n
\n
\n","html":"
\n

Introduction

\n
\n

\n Selection sort is an in-place sorting algorithm. In every\n iteration, we find the minimum value and swap it with the\n current index. That is to say that we start looping with index\n i and loop again from i+1 till the end, find the min value and\n swap it with the element at index i.\n

\n

\n This algorithm falls under Brute Force Technique which is a\n straight forward approach to solve a problem. Let's look at\n the working of this algorithm.\n

\n
\n
\n
\n

Working Procedure

\n

\n Do refer the code available the end of this section to\n understand the following theory.\n

\n
    \n
  1. Consider an array of n elements.
    2. \n
  2. Loop the array from i = 0 to n-2(Outer loop).
    3. \n
  3. Assign min = i.
    4. \n
  4. Loop the array from j = 0 to n-i-1(Inner loop).
    5. \n
  5. Assign min = j if a[j] < a[min].
    6. \n
  6. \n After the inner loop ends, if min != i then swap a[i] &\n a[min]. (It means that if we found the index of minimum value\n among the elements i+1 to n-1 then swap it with the current\n element i.e i).\n
    7. \n
  7. \n After the outer loop ends, we get the required sorted array.\n
    8. \n
\n
\n
\n

Time Complexity

\n
\n

\n PS: We give random inputs because the no. of input will\n generally be 100 or 1000 to find the time complexity and\n manually giving so many inputs is cumbersome work.\n

\n

\n The basic operation in this algorithm is the comparision\n between current element and the next element(step 5 in the\n above working procedure). So increment the count variable\n above this if condition to get the count of no. of times the\n basic operation has been performed.\n

\n \n \n \"Selection\n \n

\n Time Complexity: O(n2)\n

\n
\n
\n Similar posts:\n Bubble Sort\n
\n
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