Algorithm Learning (ii): O (n^2) sorting algorithm

Summarize the learning complexity of O (n^2) for three sorting algorithms: Select Sort, insert sort, hill sort.

(1) Select sort : From the first position start each time find the rest of the position of the smallest value into the current position;

(2) Insert sort : Starting from the second position, each time the value of the current position is inserted in the appropriate position, the insertion sort can bring more efficiency to the almost ordered sequence.

(3) Hill sort : Insert sort with variable step interval, specify a step decay rate, each wheel insert sort completes the numeric sorting of the interval specified step, and when the step decay is 1 o'clock, it becomes the standard insertion sort.

Code implementation:

(1) Select sort

var function (Arr,len) {    var  i,j,min;      for (i = 0; i < len; + +i)        {= i        ;  for (j = i + 1; j < Len; + +j)            {if(Arr[min] > arr[j])                {= j;            }        }        Swap (arr,i,min);}    };

(2) Insert sort

var function (Arr,len) {    var  i,j,k;      for (i = 1; i < Len; + +i)        {= i        ;  for (j = i-1; J >= 0;---J)            {if(Arr[j] > arr[k]) {                swap (arr,k,j);                K--;            } Else {                break;}}}    ;

(3) Hill sort

var function (arr,len,stepinterval) {    var  step,i,j,k;      for (step = Math.floor (len/stepinterval); step > 0; step = Math.floor (Step/stepinterval)) {for        (i = step; i < Len; + +i)            {= i            ;  for (j = i-step; J >= 0 && Arr[j] > Arr[k]; J -= Step) {                swap (arr,k,j)                 ; = J;            }     }}

Summarize:

(1) can be organized from different ways to help understand the playing cards, the choice of sorting is every time from the rest of the cards to take the smallest card to put the last position in the hand;

(2) The key to Hill sort is to understand that it is the insertion sort of step decay.

Algorithm Learning (ii): O (n^2) sorting algorithm