1. ► Binary search on AVL trees can be done at most in O(lgn) steps

2. ► Topological sort requires O(V) space

3. ► Merge sort works on the principle of divide-and-conquer

4. ► Heap sort cannot be done in-place

5. ► Quick sort guarantees O(nlgn) performance in all the cases

6. ► Binary search only operates on sorted sequence

7. ► Heap sort guarantees O(nlgn) performance

8. ► A simple depth-first walk is enough to give topological ordering

9. ► Merge sort can be parallelized

10. ► Merge sort is not a stable sort

11. ► Merge sort’s O(nlgn) performance is not guaranteed

12. ► In unsorted sequence, key and data cannot stay together

13. ► Heap sort doesn’t have an implementation in STL

14. ► Quick sort can be done in-place

15. ► Hidden constants are higher in merge sort

16. ► Heap sort makes use of heap data structure

17. ► Searching is more expensive in sorted sequence

18. ► A ready list can be obtained through topological sort prior to scheduling

19. ► STL doesn’t have an implementation of quick sort

20. ► Merge sort has linear space requirement