L2 · Working engineerSets~3 min · 5 tests#38

Check Two Lists Have the Same Elements

Check whether two lists contain the same distinct elements regardless of order or repeats using set equality in O(n+m). Learn when to use Counter.

The problem

Return True if a and b contain the same distinct values, ignoring order and how many times each appears.

[1, 2, 3, 3] and [3, 2, 1] → True.

Examples

Example 1

Input

same_elements([1, 2, 3, 3], [3, 2, 1])

Expected output

True

Example 2
Input
```
same_elements([1, 2], [1, 2, 4])
```
Expected output
```
False
```

+ 3 hidden tests on Submit.

Edge cases to ask about

Both empty
Repeated values
One empty

Hints

0/3

How an interviewer scores this

0/9

1. Understand the problemRestate it, ask about edge cases and input size.
2. Write a brute-force solutionCorrect first, clever later.
3. Get the correct outputautoAll visible examples pass.
4. Analyse time complexityautoCommit to a Big-O in the Complexity Lab.
5. Analyse space complexityautoExtra memory, not the input.
6. Identify the bottleneckautoMeasure your code — where does it bend?
7. OptimiseUsually: a set or dict instead of a scan.
8. Explain why it worksSay it out loud to Solvi.
9. Test the edge casesautoSubmit passes every hidden test.

Python 3.13 · same_elements

def same_elements(a, b):
    """True if a and b have the same distinct values."""
    # Write your solution here
    pass

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Complexity Lab

What does this cost as n grows?

Interviewers score the analysis as much as the code. Commit to an answer first — then check it, and measure your code against the optimal one at growing input sizes.

Time complexity of the optimal solution

Space complexity (extra memory)

Pick both to reveal the answer.

Measure it

Runs the function on inputs of size 250 up to 16,000 and records the time and peak memory. Slow solutions stop early — a short curve is itself the answer.

From brute force to optimal

The progression an interviewer wants to hear, one step at a time.

Approach	Time	Space	Idea
Sort both distinct lists	O(n log n)	O(n)
bestSet equality	O(n + m)	O(n + m)	Counts are ignored by design; use Counter if they should matter.

Walkthrough of the optimal approach (try it yourself first)

set(a) == set(b) answers "same distinct values". If the interviewer then says counts matter, switch to Counter(a) == Counter(b) — knowing the difference is the point of the question.

Complexity: O(n + m) time, O(n + m) space. Two sets are built in linear time and compared in O(min(n, m)).

Reveal the reference solution

def same_elements(a, b):
    return set(a) == set(b)

Follow-ups interviewers ask

Counts must match too.
Elements are unhashable (lists).

Frequently asked interview questions

Core interview concepts, complexities, and follow-ups scored by hiring teams.

What is the time complexity of Check Two Lists Have the Same Elements in Python?

The optimal solution runs in O(n + m) time and O(n + m) auxiliary space. Two sets are built in linear time and compared in O(min(n, m)).

What is the brute-force approach, and how do you optimise it?

Sort both distinct lists: O(n log n) time, O(n) space. Set equality: O(n + m) time, O(n + m) space. Counts are ignored by design; use Counter if they should matter.

What follow-up questions do interviewers ask about Check Two Lists Have the Same Elements?

Counts must match too. Elements are unhashable (lists).