String And Sliding Window Algorithms
Asked of: Software Engineer
Last updated

What's being tested
These problems test string scanning, substring enumeration, and sliding-window invariants under character-count, dictionary, or movement constraints. Interviewers look for whether you can reduce brute-force substring checks to linear or near-linear algorithms using counts, hashes, tries, or two pointers.
Patterns & templates
-
Sliding window with frequency counts — maintain
need,have, andformed; expand right, contract left; typicalO(n)time,O(Σ)space. -
Anagram detection via multisets — compare character counts instead of sorting each substring;
O(n * alphabet)or optimizedO(n)rolling deltas. -
Substring membership checks — use
HashSet<String>for direct lookup; for many prefixes, use a Trie or dynamic programming like word-break. -
Binary search on answer length — for longest duplicate substring, check existence with rolling hash or suffix-array-style logic; target
O(n log n). -
Movement/token invariants — scan both strings while skipping blanks; verify token order, wall positions, and directional constraints in
O(n)time. -
Multiplicity-aware coverage — minimum covering substring requires exact counts, not just presence; decrement carefully when shrinking the window.
Common pitfalls
Pitfall: Sorting every candidate substring for anagram checks often turns an intended
O(n)orO(nk)solution intoO(nk log k).
Pitfall: Treating dictionary-word checks as greedy prefix matching fails; use DP or backtracking with memoization when segmentation is ambiguous.
Pitfall: Rolling hash solutions need collision discussion; mention double hashing or final substring verification.
Practice these
The practice cards below cover the canonical variants — solve all of them and time yourself.
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Practice questions
- Implement Checksums and Feature Rollout EvaluationGoogle · Software Engineer · Take-home Project · medium
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- Check if all substrings are anagrams of wordsGoogle · Software Engineer · Technical Screen · medium
- Return dictionary words matching a prefixGoogle · Software Engineer · Technical Screen · medium
- Implement Longest-Match Text ReplacementGoogle · Software Engineer · Technical Screen · hard
- Find longest duplicated substringGoogle · Software Engineer · Technical Screen · hard
- Solve three coding interview problemsGoogle · Software Engineer · Onsite · medium
- Make algorithm code production-readyGoogle · Software Engineer · Onsite · hard
- Find minimum covering substringGoogle · Software Engineer · Onsite · Medium
- Parse strings and find meeting slotsGoogle · Software Engineer · Onsite · Medium
- Decide string transform with directional tokens and wallsGoogle · Software Engineer · Technical Screen · Medium
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