Possibly bubble sort algorithm





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$begingroup$


I'm trying to figure out what to call this sorting algorithm:






function sort(array) {
array = array.slice();

for (let i = 0; i < array.length; i++) {
for (let j = 0; j < array.length - 1; j++) {
if (array[j] > array[i]) {
//swap
[array[i], array[j]] = [array[j], array[i]]
}
}
}

return array;
}

console.log(sort([8, 4, 5, 2, 3, 7]));





I wrote it while trying to figure out bubble sort which is a lot different. Tho will have slightly the same running time as the actual bubble sort. I might be wrong :(










share|improve this question









New contributor




Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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    4












    $begingroup$


    I'm trying to figure out what to call this sorting algorithm:






    function sort(array) {
    array = array.slice();

    for (let i = 0; i < array.length; i++) {
    for (let j = 0; j < array.length - 1; j++) {
    if (array[j] > array[i]) {
    //swap
    [array[i], array[j]] = [array[j], array[i]]
    }
    }
    }

    return array;
    }

    console.log(sort([8, 4, 5, 2, 3, 7]));





    I wrote it while trying to figure out bubble sort which is a lot different. Tho will have slightly the same running time as the actual bubble sort. I might be wrong :(










    share|improve this question









    New contributor




    Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
    Check out our Code of Conduct.







    $endgroup$















      4












      4








      4


      1



      $begingroup$


      I'm trying to figure out what to call this sorting algorithm:






      function sort(array) {
      array = array.slice();

      for (let i = 0; i < array.length; i++) {
      for (let j = 0; j < array.length - 1; j++) {
      if (array[j] > array[i]) {
      //swap
      [array[i], array[j]] = [array[j], array[i]]
      }
      }
      }

      return array;
      }

      console.log(sort([8, 4, 5, 2, 3, 7]));





      I wrote it while trying to figure out bubble sort which is a lot different. Tho will have slightly the same running time as the actual bubble sort. I might be wrong :(










      share|improve this question









      New contributor




      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.







      $endgroup$




      I'm trying to figure out what to call this sorting algorithm:






      function sort(array) {
      array = array.slice();

      for (let i = 0; i < array.length; i++) {
      for (let j = 0; j < array.length - 1; j++) {
      if (array[j] > array[i]) {
      //swap
      [array[i], array[j]] = [array[j], array[i]]
      }
      }
      }

      return array;
      }

      console.log(sort([8, 4, 5, 2, 3, 7]));





      I wrote it while trying to figure out bubble sort which is a lot different. Tho will have slightly the same running time as the actual bubble sort. I might be wrong :(






      function sort(array) {
      array = array.slice();

      for (let i = 0; i < array.length; i++) {
      for (let j = 0; j < array.length - 1; j++) {
      if (array[j] > array[i]) {
      //swap
      [array[i], array[j]] = [array[j], array[i]]
      }
      }
      }

      return array;
      }

      console.log(sort([8, 4, 5, 2, 3, 7]));





      function sort(array) {
      array = array.slice();

      for (let i = 0; i < array.length; i++) {
      for (let j = 0; j < array.length - 1; j++) {
      if (array[j] > array[i]) {
      //swap
      [array[i], array[j]] = [array[j], array[i]]
      }
      }
      }

      return array;
      }

      console.log(sort([8, 4, 5, 2, 3, 7]));






      javascript algorithm sorting






      share|improve this question









      New contributor




      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      share|improve this question









      New contributor




      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      share|improve this question




      share|improve this question








      edited yesterday









      200_success

      131k17157422




      131k17157422






      New contributor




      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.









      asked yesterday









      Ademola AdegbuyiAdemola Adegbuyi

      1235




      1235




      New contributor




      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.





      New contributor





      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






      Ademola Adegbuyi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.






















          2 Answers
          2






          active

          oldest

          votes


















          4












          $begingroup$

          To me, that's exactly Bubblesort: it takes care the largest element moves to the end of the array, and then operates on length-1 elements.



          Edit: this does look quite similar to Bubblesort, but - as a diligent reader noticed - is not quite Bubblesort, as the algorithm does not compare (and swap) adjacent elements (which indeed is the main characteristic of Bubblesort). If you replace array[j] > array[i] with array[j] > array[j+1], you will get Bubblesort.



          This implementation will fail if less than two input elements are given (0 or 1) - hint: the array is already sorted in these cases (just add an if).



          A small improvement would be to add a flag in the i loop which records if any swapping happened at all - the outer for loop may terminate if the inner loop didn't perform any swaps. (Time) performance of Bubblesort is considered to be awful in comparison to other algorithms, but it must be noted it's the fastest algorithm on an already sorted array - if you add that flag ;)






          share|improve this answer











          $endgroup$









          • 1




            $begingroup$
            So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
            $endgroup$
            – Ademola Adegbuyi
            yesterday








          • 1




            $begingroup$
            No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
            $endgroup$
            – 200_success
            yesterday










          • $begingroup$
            @200_success you are absolutely right - about to edit my answer :)
            $endgroup$
            – jvb
            yesterday










          • $begingroup$
            @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
            $endgroup$
            – Ilmari Karonen
            yesterday



















          2












          $begingroup$

          It's not even obvious at a glance that your algorithm really sorts all inputs correctly. In fact, it does, but proving that takes a bit of thought.



          The key insight is that, at the end of each iteration of the outer loop, the elements at positions from 0 to i will be sorted correctly:



          for (let i = 0; i < array.length; i++) {
          for (let j = 0; j < array.length - 1; j++) {
          if (array[j] > array[i]) {
          [array[i], array[j]] = [array[j], array[i]]
          }
          }
          // Invariant: here array[0] to array[i] will be correctly sorted!
          }


          In particular, this invariant will obviously be true at the end of the first iteration, when i == 0. It is then not hard to inductively show that, if this was true at the end of the previous iteration, then it will remain true (with i now one greater than before) after the next one as well. Thus, at the end of the last iteration, with i == array.length - 1, the whole array will be correctly sorted.





          Actually, to achieve this, we only need to iterate the inner loop up to j == i - 1; the iteration with i == j obviously does nothing useful, and any later iterations of the inner loop have no effect on the invariant. (Those iterations can only swap the element currently at index i with a larger one from the tail end of the array, which will still leave array[i] greater than or equal to all its predecessors.) So we can speed up your algorithm by only iterating the inner loop until j == i:



          for (let i = 0; i < array.length; i++) {
          for (let j = 0; j < i; j++) {
          if (array[j] > array[i]) {
          [array[i], array[j]] = [array[j], array[i]]
          }
          }
          // Invariant: here array[0] to array[i] will be correctly sorted!
          }


          With this optimization, your algorithm can be recognized as a form of insertion sort.





          It's generally not the most efficient form of that algorithm, though, since the inner loop does the insertion of array[i] into its correct position somewhat inefficiently. A somewhat more efficient implementation would be something like this:



          for (let i = 1; i < array.length; i++) {
          let j = i, temp = array[i];
          while (j > 0 && array[j - 1] > temp) {
          array[j] = array[j - 1];
          j--;
          }
          if (j < i) array[j] = temp;
          // Invariant: here array[0] to array[i] will be correctly sorted!
          }


          By running the inner loop "backwards" we can stop it as soon as we find an element that's ranked lower than the one we're inserting (thus avoiding lots of needless comparisons, especially if the input array is already mostly sorted), and by saving the element to be inserted in a temporary variable, we can replace the swaps with simple assignments.



          The if (j < i) part of the code above is not really necessary, since if j == i, assigning temp back to array[i] would have no effect. That said, it's generally a useful optimization if integer comparisons are cheaper than array assignments, which is usually the case. The same goes for starting the outer loop from let i = 1 instead of let i = 0; the iteration with i == 0 does nothing anyway, so we can safely skip it!






          share|improve this answer









          $endgroup$














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            2 Answers
            2






            active

            oldest

            votes








            2 Answers
            2






            active

            oldest

            votes









            active

            oldest

            votes






            active

            oldest

            votes









            4












            $begingroup$

            To me, that's exactly Bubblesort: it takes care the largest element moves to the end of the array, and then operates on length-1 elements.



            Edit: this does look quite similar to Bubblesort, but - as a diligent reader noticed - is not quite Bubblesort, as the algorithm does not compare (and swap) adjacent elements (which indeed is the main characteristic of Bubblesort). If you replace array[j] > array[i] with array[j] > array[j+1], you will get Bubblesort.



            This implementation will fail if less than two input elements are given (0 or 1) - hint: the array is already sorted in these cases (just add an if).



            A small improvement would be to add a flag in the i loop which records if any swapping happened at all - the outer for loop may terminate if the inner loop didn't perform any swaps. (Time) performance of Bubblesort is considered to be awful in comparison to other algorithms, but it must be noted it's the fastest algorithm on an already sorted array - if you add that flag ;)






            share|improve this answer











            $endgroup$









            • 1




              $begingroup$
              So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
              $endgroup$
              – Ademola Adegbuyi
              yesterday








            • 1




              $begingroup$
              No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
              $endgroup$
              – 200_success
              yesterday










            • $begingroup$
              @200_success you are absolutely right - about to edit my answer :)
              $endgroup$
              – jvb
              yesterday










            • $begingroup$
              @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
              $endgroup$
              – Ilmari Karonen
              yesterday
















            4












            $begingroup$

            To me, that's exactly Bubblesort: it takes care the largest element moves to the end of the array, and then operates on length-1 elements.



            Edit: this does look quite similar to Bubblesort, but - as a diligent reader noticed - is not quite Bubblesort, as the algorithm does not compare (and swap) adjacent elements (which indeed is the main characteristic of Bubblesort). If you replace array[j] > array[i] with array[j] > array[j+1], you will get Bubblesort.



            This implementation will fail if less than two input elements are given (0 or 1) - hint: the array is already sorted in these cases (just add an if).



            A small improvement would be to add a flag in the i loop which records if any swapping happened at all - the outer for loop may terminate if the inner loop didn't perform any swaps. (Time) performance of Bubblesort is considered to be awful in comparison to other algorithms, but it must be noted it's the fastest algorithm on an already sorted array - if you add that flag ;)






            share|improve this answer











            $endgroup$









            • 1




              $begingroup$
              So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
              $endgroup$
              – Ademola Adegbuyi
              yesterday








            • 1




              $begingroup$
              No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
              $endgroup$
              – 200_success
              yesterday










            • $begingroup$
              @200_success you are absolutely right - about to edit my answer :)
              $endgroup$
              – jvb
              yesterday










            • $begingroup$
              @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
              $endgroup$
              – Ilmari Karonen
              yesterday














            4












            4








            4





            $begingroup$

            To me, that's exactly Bubblesort: it takes care the largest element moves to the end of the array, and then operates on length-1 elements.



            Edit: this does look quite similar to Bubblesort, but - as a diligent reader noticed - is not quite Bubblesort, as the algorithm does not compare (and swap) adjacent elements (which indeed is the main characteristic of Bubblesort). If you replace array[j] > array[i] with array[j] > array[j+1], you will get Bubblesort.



            This implementation will fail if less than two input elements are given (0 or 1) - hint: the array is already sorted in these cases (just add an if).



            A small improvement would be to add a flag in the i loop which records if any swapping happened at all - the outer for loop may terminate if the inner loop didn't perform any swaps. (Time) performance of Bubblesort is considered to be awful in comparison to other algorithms, but it must be noted it's the fastest algorithm on an already sorted array - if you add that flag ;)






            share|improve this answer











            $endgroup$



            To me, that's exactly Bubblesort: it takes care the largest element moves to the end of the array, and then operates on length-1 elements.



            Edit: this does look quite similar to Bubblesort, but - as a diligent reader noticed - is not quite Bubblesort, as the algorithm does not compare (and swap) adjacent elements (which indeed is the main characteristic of Bubblesort). If you replace array[j] > array[i] with array[j] > array[j+1], you will get Bubblesort.



            This implementation will fail if less than two input elements are given (0 or 1) - hint: the array is already sorted in these cases (just add an if).



            A small improvement would be to add a flag in the i loop which records if any swapping happened at all - the outer for loop may terminate if the inner loop didn't perform any swaps. (Time) performance of Bubblesort is considered to be awful in comparison to other algorithms, but it must be noted it's the fastest algorithm on an already sorted array - if you add that flag ;)







            share|improve this answer














            share|improve this answer



            share|improve this answer








            edited yesterday

























            answered yesterday









            jvbjvb

            899210




            899210








            • 1




              $begingroup$
              So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
              $endgroup$
              – Ademola Adegbuyi
              yesterday








            • 1




              $begingroup$
              No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
              $endgroup$
              – 200_success
              yesterday










            • $begingroup$
              @200_success you are absolutely right - about to edit my answer :)
              $endgroup$
              – jvb
              yesterday










            • $begingroup$
              @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
              $endgroup$
              – Ilmari Karonen
              yesterday














            • 1




              $begingroup$
              So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
              $endgroup$
              – Ademola Adegbuyi
              yesterday








            • 1




              $begingroup$
              No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
              $endgroup$
              – 200_success
              yesterday










            • $begingroup$
              @200_success you are absolutely right - about to edit my answer :)
              $endgroup$
              – jvb
              yesterday










            • $begingroup$
              @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
              $endgroup$
              – Ilmari Karonen
              yesterday








            1




            1




            $begingroup$
            So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
            $endgroup$
            – Ademola Adegbuyi
            yesterday






            $begingroup$
            So, I visualized the execution on pythontutor.com. One should "never" use this. It's worse than the unoptimized version of bubble sort. I goes forth and back, which takes more time. Thanks!
            $endgroup$
            – Ademola Adegbuyi
            yesterday






            1




            1




            $begingroup$
            No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
            $endgroup$
            – 200_success
            yesterday




            $begingroup$
            No. One of the defining characteristics of Bubble sort is that it swaps adjacent elements — which is not the case with this code.
            $endgroup$
            – 200_success
            yesterday












            $begingroup$
            @200_success you are absolutely right - about to edit my answer :)
            $endgroup$
            – jvb
            yesterday




            $begingroup$
            @200_success you are absolutely right - about to edit my answer :)
            $endgroup$
            – jvb
            yesterday












            $begingroup$
            @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
            $endgroup$
            – Ilmari Karonen
            yesterday




            $begingroup$
            @200_success: The OP's code is actually a (rather inefficient) variant of insertion sort, with some mostly useless extra shuffling of the tail end of the array thrown in.
            $endgroup$
            – Ilmari Karonen
            yesterday













            2












            $begingroup$

            It's not even obvious at a glance that your algorithm really sorts all inputs correctly. In fact, it does, but proving that takes a bit of thought.



            The key insight is that, at the end of each iteration of the outer loop, the elements at positions from 0 to i will be sorted correctly:



            for (let i = 0; i < array.length; i++) {
            for (let j = 0; j < array.length - 1; j++) {
            if (array[j] > array[i]) {
            [array[i], array[j]] = [array[j], array[i]]
            }
            }
            // Invariant: here array[0] to array[i] will be correctly sorted!
            }


            In particular, this invariant will obviously be true at the end of the first iteration, when i == 0. It is then not hard to inductively show that, if this was true at the end of the previous iteration, then it will remain true (with i now one greater than before) after the next one as well. Thus, at the end of the last iteration, with i == array.length - 1, the whole array will be correctly sorted.





            Actually, to achieve this, we only need to iterate the inner loop up to j == i - 1; the iteration with i == j obviously does nothing useful, and any later iterations of the inner loop have no effect on the invariant. (Those iterations can only swap the element currently at index i with a larger one from the tail end of the array, which will still leave array[i] greater than or equal to all its predecessors.) So we can speed up your algorithm by only iterating the inner loop until j == i:



            for (let i = 0; i < array.length; i++) {
            for (let j = 0; j < i; j++) {
            if (array[j] > array[i]) {
            [array[i], array[j]] = [array[j], array[i]]
            }
            }
            // Invariant: here array[0] to array[i] will be correctly sorted!
            }


            With this optimization, your algorithm can be recognized as a form of insertion sort.





            It's generally not the most efficient form of that algorithm, though, since the inner loop does the insertion of array[i] into its correct position somewhat inefficiently. A somewhat more efficient implementation would be something like this:



            for (let i = 1; i < array.length; i++) {
            let j = i, temp = array[i];
            while (j > 0 && array[j - 1] > temp) {
            array[j] = array[j - 1];
            j--;
            }
            if (j < i) array[j] = temp;
            // Invariant: here array[0] to array[i] will be correctly sorted!
            }


            By running the inner loop "backwards" we can stop it as soon as we find an element that's ranked lower than the one we're inserting (thus avoiding lots of needless comparisons, especially if the input array is already mostly sorted), and by saving the element to be inserted in a temporary variable, we can replace the swaps with simple assignments.



            The if (j < i) part of the code above is not really necessary, since if j == i, assigning temp back to array[i] would have no effect. That said, it's generally a useful optimization if integer comparisons are cheaper than array assignments, which is usually the case. The same goes for starting the outer loop from let i = 1 instead of let i = 0; the iteration with i == 0 does nothing anyway, so we can safely skip it!






            share|improve this answer









            $endgroup$


















              2












              $begingroup$

              It's not even obvious at a glance that your algorithm really sorts all inputs correctly. In fact, it does, but proving that takes a bit of thought.



              The key insight is that, at the end of each iteration of the outer loop, the elements at positions from 0 to i will be sorted correctly:



              for (let i = 0; i < array.length; i++) {
              for (let j = 0; j < array.length - 1; j++) {
              if (array[j] > array[i]) {
              [array[i], array[j]] = [array[j], array[i]]
              }
              }
              // Invariant: here array[0] to array[i] will be correctly sorted!
              }


              In particular, this invariant will obviously be true at the end of the first iteration, when i == 0. It is then not hard to inductively show that, if this was true at the end of the previous iteration, then it will remain true (with i now one greater than before) after the next one as well. Thus, at the end of the last iteration, with i == array.length - 1, the whole array will be correctly sorted.





              Actually, to achieve this, we only need to iterate the inner loop up to j == i - 1; the iteration with i == j obviously does nothing useful, and any later iterations of the inner loop have no effect on the invariant. (Those iterations can only swap the element currently at index i with a larger one from the tail end of the array, which will still leave array[i] greater than or equal to all its predecessors.) So we can speed up your algorithm by only iterating the inner loop until j == i:



              for (let i = 0; i < array.length; i++) {
              for (let j = 0; j < i; j++) {
              if (array[j] > array[i]) {
              [array[i], array[j]] = [array[j], array[i]]
              }
              }
              // Invariant: here array[0] to array[i] will be correctly sorted!
              }


              With this optimization, your algorithm can be recognized as a form of insertion sort.





              It's generally not the most efficient form of that algorithm, though, since the inner loop does the insertion of array[i] into its correct position somewhat inefficiently. A somewhat more efficient implementation would be something like this:



              for (let i = 1; i < array.length; i++) {
              let j = i, temp = array[i];
              while (j > 0 && array[j - 1] > temp) {
              array[j] = array[j - 1];
              j--;
              }
              if (j < i) array[j] = temp;
              // Invariant: here array[0] to array[i] will be correctly sorted!
              }


              By running the inner loop "backwards" we can stop it as soon as we find an element that's ranked lower than the one we're inserting (thus avoiding lots of needless comparisons, especially if the input array is already mostly sorted), and by saving the element to be inserted in a temporary variable, we can replace the swaps with simple assignments.



              The if (j < i) part of the code above is not really necessary, since if j == i, assigning temp back to array[i] would have no effect. That said, it's generally a useful optimization if integer comparisons are cheaper than array assignments, which is usually the case. The same goes for starting the outer loop from let i = 1 instead of let i = 0; the iteration with i == 0 does nothing anyway, so we can safely skip it!






              share|improve this answer









              $endgroup$
















                2












                2








                2





                $begingroup$

                It's not even obvious at a glance that your algorithm really sorts all inputs correctly. In fact, it does, but proving that takes a bit of thought.



                The key insight is that, at the end of each iteration of the outer loop, the elements at positions from 0 to i will be sorted correctly:



                for (let i = 0; i < array.length; i++) {
                for (let j = 0; j < array.length - 1; j++) {
                if (array[j] > array[i]) {
                [array[i], array[j]] = [array[j], array[i]]
                }
                }
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                In particular, this invariant will obviously be true at the end of the first iteration, when i == 0. It is then not hard to inductively show that, if this was true at the end of the previous iteration, then it will remain true (with i now one greater than before) after the next one as well. Thus, at the end of the last iteration, with i == array.length - 1, the whole array will be correctly sorted.





                Actually, to achieve this, we only need to iterate the inner loop up to j == i - 1; the iteration with i == j obviously does nothing useful, and any later iterations of the inner loop have no effect on the invariant. (Those iterations can only swap the element currently at index i with a larger one from the tail end of the array, which will still leave array[i] greater than or equal to all its predecessors.) So we can speed up your algorithm by only iterating the inner loop until j == i:



                for (let i = 0; i < array.length; i++) {
                for (let j = 0; j < i; j++) {
                if (array[j] > array[i]) {
                [array[i], array[j]] = [array[j], array[i]]
                }
                }
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                With this optimization, your algorithm can be recognized as a form of insertion sort.





                It's generally not the most efficient form of that algorithm, though, since the inner loop does the insertion of array[i] into its correct position somewhat inefficiently. A somewhat more efficient implementation would be something like this:



                for (let i = 1; i < array.length; i++) {
                let j = i, temp = array[i];
                while (j > 0 && array[j - 1] > temp) {
                array[j] = array[j - 1];
                j--;
                }
                if (j < i) array[j] = temp;
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                By running the inner loop "backwards" we can stop it as soon as we find an element that's ranked lower than the one we're inserting (thus avoiding lots of needless comparisons, especially if the input array is already mostly sorted), and by saving the element to be inserted in a temporary variable, we can replace the swaps with simple assignments.



                The if (j < i) part of the code above is not really necessary, since if j == i, assigning temp back to array[i] would have no effect. That said, it's generally a useful optimization if integer comparisons are cheaper than array assignments, which is usually the case. The same goes for starting the outer loop from let i = 1 instead of let i = 0; the iteration with i == 0 does nothing anyway, so we can safely skip it!






                share|improve this answer









                $endgroup$



                It's not even obvious at a glance that your algorithm really sorts all inputs correctly. In fact, it does, but proving that takes a bit of thought.



                The key insight is that, at the end of each iteration of the outer loop, the elements at positions from 0 to i will be sorted correctly:



                for (let i = 0; i < array.length; i++) {
                for (let j = 0; j < array.length - 1; j++) {
                if (array[j] > array[i]) {
                [array[i], array[j]] = [array[j], array[i]]
                }
                }
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                In particular, this invariant will obviously be true at the end of the first iteration, when i == 0. It is then not hard to inductively show that, if this was true at the end of the previous iteration, then it will remain true (with i now one greater than before) after the next one as well. Thus, at the end of the last iteration, with i == array.length - 1, the whole array will be correctly sorted.





                Actually, to achieve this, we only need to iterate the inner loop up to j == i - 1; the iteration with i == j obviously does nothing useful, and any later iterations of the inner loop have no effect on the invariant. (Those iterations can only swap the element currently at index i with a larger one from the tail end of the array, which will still leave array[i] greater than or equal to all its predecessors.) So we can speed up your algorithm by only iterating the inner loop until j == i:



                for (let i = 0; i < array.length; i++) {
                for (let j = 0; j < i; j++) {
                if (array[j] > array[i]) {
                [array[i], array[j]] = [array[j], array[i]]
                }
                }
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                With this optimization, your algorithm can be recognized as a form of insertion sort.





                It's generally not the most efficient form of that algorithm, though, since the inner loop does the insertion of array[i] into its correct position somewhat inefficiently. A somewhat more efficient implementation would be something like this:



                for (let i = 1; i < array.length; i++) {
                let j = i, temp = array[i];
                while (j > 0 && array[j - 1] > temp) {
                array[j] = array[j - 1];
                j--;
                }
                if (j < i) array[j] = temp;
                // Invariant: here array[0] to array[i] will be correctly sorted!
                }


                By running the inner loop "backwards" we can stop it as soon as we find an element that's ranked lower than the one we're inserting (thus avoiding lots of needless comparisons, especially if the input array is already mostly sorted), and by saving the element to be inserted in a temporary variable, we can replace the swaps with simple assignments.



                The if (j < i) part of the code above is not really necessary, since if j == i, assigning temp back to array[i] would have no effect. That said, it's generally a useful optimization if integer comparisons are cheaper than array assignments, which is usually the case. The same goes for starting the outer loop from let i = 1 instead of let i = 0; the iteration with i == 0 does nothing anyway, so we can safely skip it!







                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered yesterday









                Ilmari KaronenIlmari Karonen

                1,865915




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