<Tr> <Th_colspan="2"> Time complexity in big O notation </Th> </Tr> <Tr> <Td_colspan="2"> <Table> <Tr> <Th> Algorithm </Th> <Td> </Td> <Td> Average </Td> <Td> Worst case </Td> </Tr> <Tr> <Th> Insert </Th> <Td> </Td> <Td> O (log n) </Td> <Td> O (log n) </Td> </Tr> <Tr> <Th> Delete </Th> <Td> </Td> <Td> O (log n) </Td> <Td> O (log n) </Td> </Tr> </Table> </Td> </Tr> <Table> <Tr> <Th> Algorithm </Th> <Td> </Td> <Td> Average </Td> <Td> Worst case </Td> </Tr> <Tr> <Th> Insert </Th> <Td> </Td> <Td> O (log n) </Td> <Td> O (log n) </Td> </Tr> <Tr> <Th> Delete </Th> <Td> </Td> <Td> O (log n) </Td> <Td> O (log n) </Td> </Tr> </Table> <Tr> <Th> Algorithm </Th> <Td> </Td> <Td> Average </Td> <Td> Worst case </Td> </Tr>

Minimum of a heap can be found in constant time