Sorts this list according to the order induced by the specified Comparator.

All elements in this list must be mutually comparable using the specified comparator (that is, c.compare(e1, e2) must not throw a ClassCastException for any elements e1 and e2 in the list).

If the specified comparator is null then all elements in this list must implement the Comparable interface and the elements' natural ordering should be used.

This list must be modifiable, but need not be resizable.

Parameters:

c

the Comparator used to compare list elements. A null value indicates that the elements' natural ordering should be used

Exceptions:

ClassCastException		if the list contains elements that are not mutually comparable using the specified comparator
UnsupportedOperationException		if the list's list-iterator does not support the set operation
IllegalArgumentException		(optional) if the comparator is found to violate the Comparator contract

Since:  1.8

@implSpec The default implementation obtains an array containing all elements in this list, sorts the array, and iterates over this list resetting each element from the corresponding position in the array. (This avoids the n² log(n) performance that would result from attempting to sort a linked list in place.)
@implNote This implementation is a stable, adaptive, iterative mergesort that requires far fewer than n lg(n) comparisons when the input array is partially sorted, while offering the performance of a traditional mergesort when the input array is randomly ordered. If the input array is nearly sorted, the implementation requires approximately n comparisons. Temporary storage requirements vary from a small constant for nearly sorted input arrays to n/2 object references for randomly ordered input arrays.

The implementation takes equal advantage of ascending and descending order in its input array, and can take advantage of ascending and descending order in different parts of the same input array. It is well-suited to merging two or more sorted arrays: simply concatenate the arrays and sort the resulting array.

The implementation was adapted from Tim Peters's list sort for Python ( TimSort). It uses techniques from Peter McIlroy's "Optimistic Sorting and Information Theoretic Complexity", in Proceedings of the Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, pp 467-474, January 1993.