Rearrange Spaces Between Words
Time O(n) · Space O(1) · Official statement on LeetCode
Solutions
// Time: O(n)
// Space: O(1)
// inplace solution
class Solution {
public:
string reorderSpaces(string text) {
// count spaces and words
int space_count = 0, word_count = 0;
for (int i = 0; i < size(text); ++i) {
if (text[i] == ' ') {
++space_count;
} else if (i == 0 || text[i - 1] == ' ') {
++word_count;
}
}
// rearrange the spaces to the right
int left = 0, curr = 0;
for (int i = 0; i < size(text); ++i) {
bool has_word = false;
while (i < size(text) && text[i] != ' ') {
swap(text[left++], text[i++]);
has_word = true;
}
if (has_word) {
++left; // keep one space
}
}
// rearrange the spaces to the left
int equal_count = word_count - 1 > 0 ? space_count / (word_count - 1) : 0;
int extra_count = word_count - 1 > 0 ? space_count % (word_count - 1) : space_count;
int right = size(text) - 1 - extra_count;
for (int i = size(text) - 1; i >= 0; --i) {
bool has_word = false;
while (i >= 0 && text[i] != ' ') {
swap(text[right--], text[i--]);
has_word = true;
}
if (has_word) {
right -= equal_count; // keep equal_count spaces
}
}
return text;
}
};
Beginner Explanation
What is Rearrange Spaces Between Words?
Rearrange Spaces Between Words (LeetCode #1592) is a Easy problem that primarily trains string.
How to think about it
- Restate the goal in your own words before coding.
- Work a tiny example by hand so the invariant becomes obvious.
- Identify the pattern — this problem aligns with general problem-solving.
- Only then translate the idea into code.
Why this problem matters
It builds core muscle memory you will reuse on harder variants. Official solution notes mention: Inplace.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Rearrange Spaces Between Words
Opening (30–60 seconds)
- Clarify inputs/outputs and edge cases (empty input, single element, duplicates, overflow).
- State a brute force so the interviewer knows you can solve it naively.
- Propose the optimal direction tied to general problem-solving.
Core solution narrative
- Define the state you track (pointers, DP cell, set membership, stack top, etc.).
- Explain the transition when you process the next element.
- Call out time (O(n)) and space (O(1)) before coding.
- Code cleanly; narrate variable names.
What interviewers listen for
- Correctness on edge cases
- Complexity honesty
- Ability to discuss trade-offs (e.g., hash map space vs. sort + two pointers)
Follow-up questions they may ask
- Can you solve it with less memory?
- What if the input stream is infinite / doesn't fit in RAM?
- How would tests look for adversarial inputs?
Optimized Approach
Optimized solution notes
The reference solutions on AlgoForge target O(n) time and O(1) space.
Pattern focus: general problem-solving
Use the pattern as a checklist:
- Identify the dominant pattern and stick to one clear invariant
Start from the primary solution, then rewrite from memory to lock it in.
Implementation tips
- Prefer readable names over micro-optimizations in interviews.
- Extract helpers only when they clarify (e.g., expand-around-center, DFS visit).
- After AC-level logic, re-scan for off-by-one and null checks.
Complexity Analysis
Complexity
| Measure | Bound |
|---|---|
| Time | O(n) |
| Space | O(1) |
How to justify this in an interview
- Time: count loops, map/set operations, and recursive branching; state average vs worst case if relevant.
- Space: include hash maps, recursion stack, and output allocation when the problem asks for it.
If your implementation differs from the reference, re-derive big-O from your code — never memorize a complexity you cannot defend.
Common Mistakes
Common mistakes on Rearrange Spaces Between Words
- Skipping edge cases — empty collections, single-element inputs, max constraints.
- Wrong invariant for general problem-solving — updating state too early or too late.
- Mutating input unexpectedly when the problem forbids it.
- Off-by-one in windows, ranges, or binary search bounds.
- Ignoring overflow / precision for integer arithmetic problems.
- Overengineering — jumping to an advanced structure when a simpler approach works.
Alternative Approaches
AI expand laterAlternatives
Placeholder for multi-approach comparison. Future AI content generation can expand:
- Brute force baseline
- Optimal general problem-solving solution
- Space-optimized rewrite
Prompt slot: expand alternatives for rearrange-spaces-between-words.
Edge Cases
Edge cases checklist
- Minimum input size
- Maximum input size / time limits
- Duplicates and already-sorted input
- Negative numbers / zeros (if applicable)
- Disconnected structures (graphs/trees)
- Single path vs branching recursion depth
Pattern Recognition
Spotting this pattern
Signal phrases that point to general problem-solving:
- Sorted input or ability to sort without changing the answer class
- Need for contiguous subarray / substring → consider sliding window
- Need for O(1) membership → hash set/map
- Optimal substructure + overlapping subproblems → DP
- Connectivity / components → graph DFS/BFS or Union-Find
Primary topics: string.
Follow-up Interview Questions
Follow-ups
- How does the solution change if the input is a stream?
- Can you solve it in-place?
- What if duplicates must be handled differently?
- How would you parallelize the approach?
- Design tests that would break a buggy implementation.
Practice Recommendations
What to practice next
- Re-solve Rearrange Spaces Between Words in a second language (cpp, python).
- Drill 3–5 more problems tagged string.
- Teach the solution out loud in under 5 minutes.
- Add this problem to your revision calendar in 3 days and 14 days.
Visualization
Study checklist
- Read the official problem statement on LeetCode
- Solve on paper / whiteboard first
- Implement the general problem-solving approach
- Verify edge cases from the checklist
- State time and space complexity aloud
- Compare with the AlgoForge reference solution
- Schedule a revision session
Revision notes
Rearrange Spaces Between Words (#1592) — Easy. Pattern: general problem-solving. Complexity: O(n) time / O(1) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Rearrange Spaces Between Words?+
The reference solutions aim for O(n) time and O(1) space. Always re-derive complexity from the code you write in the interview.
What pattern does Rearrange Spaces Between Words use?+
It primarily maps to general problem-solving, within the broader topic of string.
Is Rearrange Spaces Between Words good for interviews?+
Yes — as a Easy problem it is a solid practice target. Pair it with related problems in the same pattern family for spaced repetition.
Where can I read the official statement?+
Open the official LeetCode page for constraints and examples: https://leetcode.com/problems/rearrange-spaces-between-words/