1. ► Big-O notation has no hidden constant

2. ► Greedy algorithm doesn’t guarantee global optimal

3. ► Binary search only operates on sorted sequence

4. ► Good data structure make programs more efficient

5. ► Smaller order terms cannot be ignored in analysis for small data set

6. ► Data structure needing large contiguous memory might fail to work even if that much memory is available

7. ► Exact figures of memory usage is not important

8. ► Topological sort requires O(V) space

9. ► Connected component algorithm is there in boost library

10. ► Brute force string matching relies on char by char comparison

11. ► Average case complexity of Rabin-Karp is O(nm)

12. ► Frequent cheap operations compensate expensive operations

13. ► Greedy algorithms always select local best possible solution

14. ► Rabin-Karp algorithm relies on hash function to convert strings to numbers

15. ► Amortized analysis is applicable when there is certain relationship between cheap and expensive operations