Combo Sort is a relatively straightforward sorting algorithm that improves
upon the traditional Bubble Sort by utilizing a gap during comparisons and
swaps. The algorithm was devised by Włodzimierz Dobosiewicz and Artur Borowy
in 1980 and its design aims to eliminate turtles, which are small values at
the end of the list that slow down the sorting process in Bubble Sort.
Time Complexity:
Best Case: O (n log n) - This happens in scenarios where the input data
is partially sorted. Combo Sort tends to have a slightly better best-case time
complexity compared to Bubble Sort due to the use of a gap that can be larger
than 1, thereby reducing the number of overall comparisons and swaps.
Average Case: O (n^2/2^p), where p is the number of increments The time
complexity in the average case is hard to determine without specific details
about the distribution of input data and is typically approximated because it
depends on the 'shrink factor' used to decrement the gap and how the data is
arranged. The factor of 2^p in the denominator represents the number of
passes, which is influenced by how quickly the gap size reduces.
Worst Case: O (n^2), This is often considered to be quadratic O (n^2)
specially when dealing with reverse-ordered data or data with many duplicates.
However, it's essential to note that Combo Sort is generally slightly more
efficient than a traditional Bubble Sort due to its ability to move items
quickly to their correct position in the early stages when the gap is large.
Combo Sort is a relatively straightforward sorting algorithm that improves upon the traditional Bubble Sort by utilizing a gap during comparisons and swaps. The algorithm was devised by Włodzimierz Dobosiewicz and Artur Borowy in 1980 and its design aims to eliminate turtles, which are small values at the end of the list that slow down the sorting process in Bubble Sort.
Time Complexity:
Best Case: O (n log n) - This happens in scenarios where the input data is partially sorted. Combo Sort tends to have a slightly better best-case time complexity compared to Bubble Sort due to the use of a gap that can be larger than 1, thereby reducing the number of overall comparisons and swaps.
Average Case: O (n^2/2^p), where p is the number of increments The time complexity in the average case is hard to determine without specific details about the distribution of input data and is typically approximated because it depends on the 'shrink factor' used to decrement the gap and how the data is arranged. The factor of 2^p in the denominator represents the number of passes, which is influenced by how quickly the gap size reduces.
Worst Case: O (n^2), This is often considered to be quadratic O (n^2) specially when dealing with reverse-ordered data or data with many duplicates. However, it's essential to note that Combo Sort is generally slightly more efficient than a traditional Bubble Sort due to its ability to move items quickly to their correct position in the early stages when the gap is large.
Space Complexity: O(1)