Code optimisation

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Quick Questions

Shade in the A or B circle for each question.

1. Which best describes code optimisation?

A Adding new features so the program does more

B Improving speed, memory use or readability without changing what the program does

2. A program has the same 4 lines copied three times. What is the best optimisation?

A Add a comment above each copy of the lines

B Move the repeated lines into a function and call it three times

3. Which is the better way to add up the numbers in a list called scores?

A total = sum(scores)

B Write out scores[0] + scores[1] + scores[2] + ... by hand

4. A sorted list of 1,000,000 items needs to be searched. Which is the better algorithm?

A Binary search

B Linear search

5. Which statement about optimisation is true?

A Optimised code must still give the same output as the original

B Optimised code is allowed to give different output if it runs faster

Match the Pairs

Draw a line connecting each item on the left to its match on the right.

Left column		Right column
1total = sum(marks)		Amid = (low + high) // 2
2def show(x): print(x * 2)		Blen(names) is recalculated on every pass of the loop instead of being stored once in a variable
3Choosing a better algorithm: binary search on a sorted list is faster than checking every item		CUses a built-in function to add up a list, replacing a longer hand-written loop
4Readability vs speed: a clear variable name makes code easier to maintain even if it is not faster		Daverage_mark = total / count
5for i in range(len(names)): print(len(names))		EMoves repeated code into one function that can be called many times
6print(a * 2) print(b * 2) print(c * 2)		FThe same calculation is copied three times instead of using a loop or function to remove the repeated code

Definitions

optimisation

Fill in the Blanks

Complete each line of code by filling in the missing parts.

total = ___(marks)

for i in _____(5): print("Hello")

mid = (low + high) __ 2

ordered = ______(scores)

limit = len(items) while i < _____:

Spot the Error

Shade in the letter of the line that contains an error.

Question 1

A marks = [72, 88, 65, 91]

B total = sum(marks)

C average = total / len(total)

D print(average)

Question 2

A names = ['Ava', 'Liam']

B for name in len(names):

C print('Hi', name)

Question 3

A def total(items)

B return sum(items)

C print(total([4, 8, 15]))

Question 4

A nums = [3, 9, 4, 7]

B low = min(nums)

C high = max(nums)

D print(high - lows)

Question 5

A define find(items, x):

B if x in items:

C return items.index(x)

D return -1

Answer Key

Code optimisation

Section A: Quick Questions

B — Improving speed, memory use or readability without changing what the program does

B — Move the repeated lines into a function and call it three times

A — total = sum(scores)

A — Binary search

A — Optimised code must still give the same output as the original

Section B: Match the Pairs

total = sum(marks) → Uses a built-in function to add up a list, replacing a longer hand-written loop

def show(x): print(x * 2) → Moves repeated code into one function that can be called many times

Choosing a better algorithm: binary search on a sorted list is faster than checking every item → mid = (low + high) // 2

Readability vs speed: a clear variable name makes code easier to maintain even if it is not faster → average_mark = total / count

for i in range(len(names)): print(len(names)) → len(names) is recalculated on every pass of the loop instead of being stored once in a variable

print(a * 2) print(b * 2) print(c * 2) → The same calculation is copied three times instead of using a loop or function to remove the repeated code

Section C: Definitions

optimisation — Changing code so it runs faster, uses less memory or is easier to read, without changing what it does. For example, removing repeated code or using a built-in function.

Section D: Fill in the Blanks

total = sum(marks)

for i in range(5):
    print("Hello")

mid = (low + high) // 2

ordered = sorted(scores)

limit = len(items)
while i < limit:

Section E: Spot the Error

C — len() needs a list, but total is a single number, so this causes a TypeError. Using the built-in sum() is a good optimisation, but the average must divide by len(marks).

B — len(names) is a number and cannot be looped over, so this causes a TypeError. A loop replaces repeated print lines, but it must loop over the list itself: for name in names:

A — A function header must end with a colon. Putting the repeated work in one function removes duplicated code, but the header must be def total(items):

D — The variable lows was never created, so this causes a NameError. The built-in min() and max() store the values in low and high, so the line should be print(high - low).

A — Python uses the keyword def, not define, to create a function. Using built-in in and .index() is shorter than writing your own loop, but the header must be def find(items, x):