lab_encoding/questions.md

Boolean questions

Create the following variables.

a = Bits("11110000")
b = Bits("10101010")

For each of the following bytes, give an equivalent expression which uses only a, b, and bit operators. The answers to the first two questions are given.

1. 01010101

~b

2. 00000101

~a & ~b

3. 00000001

a >> 7

4. 10000000

a << 3

5. 01010000

(a & b) >>1

6. 00001010

(~a) & b

7. 01010000 #this is the same as #5...

((~a) & b) << 3

8. 10101011

(a >> 7) | b

Integer questions

These questions are difficult! Try exploring ideas with Bits in Terminal, a paper and pencil, and a whiteboard. And definitely talk with others.

9. If a represents a positive integer, and one = Bits(1, length=len(a)), give an expression equivalent to -a, but which does not use negation.

~a + Bits(1, length = len(a))

10. It is extremely easy to double a binary number: just shift all the bits to the left. (a << 1 is twice a.) Explain why this trick works.

From a math approach, binary is writing numbers in base 2, so each 0/1 represents a power of 2, increasing as you go to the left. For example, 00000101 = 5, beacuse its 2^2 + 2^0 = 4 + 1 = 5. So every time you shift the binary numbers once to the left, you are introducing a new power of 2, or effectively multiplying by 2.

11. Consider the following:

>>> hundred = Bits(100, 8)
>>> hundred
01100100
>>> (hundred + hundred)
11001000
>>> (hundred + hundred).int
-56

Apparently 100 + 100 = -56. What's going on here?

Since we are only using 8 bits, the highest possible positive number we can represent is 127 (just shy of 2^7, which is 128, because we can only represent up to 2^7 with 8 digits). When you do the bitwise addition, you end up with a 1 as the first bit, which signals to the computer that this is a negative number. In other words, you can't do proper integer addition in 8 bits with a positive result higher than 127, because it cannot be represented in 8 bits.

12. What is the bit representation of negative zero? Explain your answer.

I was a bit hesitant about this one, because my math brain tells me that there is no such thing as negative 0, so I tried Bits(0,8) and Bits(-0,8) and turns out I was right, they are both 00000000.

13. What's the largest integer that can be represented in a single byte? Explain your reasoning.

    Oh I already did this one! It's 127, see my reasoning above.

14. What's the smallest integer that can be represented in a single byte? Explain your reasoning.

    -128, similarly to above. This is represented by 10000000, which is effectively the inverse of 127, but minus 1 (which are the steps for finding the negative)

15. What's the largest integer that can be represented in n bits? Explain your reasoning.

(2^(n-1))-1. Similar reasoning to how I got 127, because it will be one less than the highest power of 2 made from the given powers. Yay math questions!

Text questions

16. Look at the bits for a few different characters using the utf8 encoding. You will notice they have different bit lengths:

    >>> Bits('a', encoding='utf8')
    01100001
    >>> Bits('ñ', encoding='utf8')
    1100001110110001
    >>> Bits('♣', encoding='utf8')
    111000101001100110100011
    >>> Bits('😍', encoding='utf8')
    11110000100111111001100010001101
    

    When it's time to decode a sequence of utf8-encoded bits, the decoder somehow needs to decide when it has read enough bits to decode a character, and when it needs to keep reading. For example, the decoder will produce 'a' after reading 8 bits but after reading the first 8 bits of 'ñ', the decoder realizes it needs to read 8 more bits.

    Make a hypothesis about how this could work.