Answer:
The five eras are general- purpose mainframe and minicomputer computing, personal computers, client/server networks, ...
Answer:1. Introduction to Python
1.1 A Simple Python Program
1.2 Creating and Running a Python Program
2. Virtual Data Storage
3. Statement Types
3.1 Input/Output Statements
3.2 The Assignment Statement
3.3 Control Statements
4. Another Example
5. Managing Complexity
5.1 Divide and Conquer
5.2 Using and Writing Functions
6. Object-Oriented Programming
6.1 What Is It?
6.2 Python and OOP
6.3 One More Example
6.4 What Have We Gained?
7. Graphical Programming
7.1 Graphics Hardware
7.2 Graphics Software
8. Conclusion
E X E R C I S E S
A N S W E R S T O P R A C T I C E P R O B L E M S
Explanation: I got you bruv.
Answer:
O(N!), O(2N), O(N2), O(N), O(logN)
Explanation:
N! grows faster than any exponential functions, leave alone polynomials and logarithm. so O( N! ) would be slowest.
2^N would be bigger than N². Any exponential functions are slower than polynomial. So O( 2^N ) is next slowest.
Rest of them should be easier.
N² is slower than N and N is slower than logN as you can check in a graphing calculator.
NOTE: It is just nitpick but big-Oh is not necessary about speed / running time ( many programmers treat it like that anyway ) but rather how the time taken for an algorithm increase as the size of the input increases. Subtle difference.
Answer:
function sum(number) {
if (number == 1) {
return 1;
}
return number + sum(number -1);
}
Explanation:
This is a recursive function, it means that is a function that calls itself for example: if you call the function with sum(5) the process is :
sum(5)
|______ 5 + sum(4)
|_______ 4 + sum(3)
|______ 3 + sum(2)
|_____2 + sum(1)
|_____ 1
the result is 1+2+3+4+5 = 15
