Check If a Word Occurs As a Prefix of Any Word in a Sentence
Time O(n) · Space O(n) · Official statement on LeetCode
Solutions
// Time: O(n)
// Space: O(n)
class Solution {
public:
int isPrefixOfWord(string sentence, string searchWord) {
if (sentence.compare(0, searchWord.size(), searchWord) == 0) {
return 1;
}
searchWord = " " + searchWord;
auto p = KMP(sentence, searchWord);
if (p == -1) {
return -1;
}
return 1 + accumulate(cbegin(sentence), cbegin(sentence) + p + 1, 0,
[](const auto& a, const auto& b) {
return a + (b == ' ');
});
}
private:
int KMP(const string& text, const string& pattern) {
const vector<int> prefix = getPrefix(pattern);
int j = -1;
for (int i = 0; i < text.length(); ++i) {
while (j > -1 && pattern[j + 1] != text[i]) {
j = prefix[j];
}
if (pattern[j + 1] == text[i]) {
++j;
}
if (j == pattern.length() - 1) {
return i - j;
}
}
return -1;
}
vector<int> getPrefix(const string& pattern) {
vector<int> prefix(pattern.length(), -1);
int j = -1;
for (int i = 1; i < pattern.length(); ++i) {
while (j > -1 && pattern[j + 1] != pattern[i]) {
j = prefix[j];
}
if (pattern[j + 1] == pattern[i]) {
++j;
}
prefix[i] = j;
}
return prefix;
}
};
Beginner Explanation
What is Check If a Word Occurs As a Prefix of Any Word in a Sentence?
Check If a Word Occurs As a Prefix of Any Word in a Sentence (LeetCode #1455) 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 kmp algorithm.
- 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: KMP Algorithm.
AlgoForge explanations are original teaching notes. Always open the official problem statement on LeetCode for constraints and examples.
Interview Walkthrough
Interview approach for Check If a Word Occurs As a Prefix of Any Word in a Sentence
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 kmp algorithm.
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(n)) 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(n) space.
Pattern focus: kmp algorithm
Use the pattern as a checklist:
- kmp algorithm — confirm the invariant holds after each step
Multiple methods appear in the source solutions — compare them and explain when each is preferable.
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(n) |
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 Check If a Word Occurs As a Prefix of Any Word in a Sentence
- Skipping edge cases — empty collections, single-element inputs, max constraints.
- Wrong invariant for kmp algorithm — 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
Alternatives
The source file includes more than one method. Compare:
- Primary optimized path — best complexity for typical interviews.
- Secondary approach — often brute force, sorting-based, or space-optimized variant.
Practice articulating when you would pick each (constraints, readability, follow-ups).
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 kmp algorithm:
- 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 Check If a Word Occurs As a Prefix of Any Word in a Sentence 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 kmp algorithm 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
Check If a Word Occurs As a Prefix of Any Word in a Sentence (#1455) — Easy. Pattern: kmp algorithm. Complexity: O(n) time / O(n) space. Re-derive the invariant before coding.
FAQs
What is the time complexity of Check If a Word Occurs As a Prefix of Any Word in a Sentence?+
The reference solutions aim for O(n) time and O(n) space. Always re-derive complexity from the code you write in the interview.
What pattern does Check If a Word Occurs As a Prefix of Any Word in a Sentence use?+
It primarily maps to kmp algorithm, within the broader topic of string.
Is Check If a Word Occurs As a Prefix of Any Word in a Sentence 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/check-if-a-word-occurs-as-a-prefix-of-any-word-in-a-sentence/