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Grammarly·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Jun 2026

Summary

Phone screen for a Software Engineer role at Grammarly. Three coding questions back to back, all string or interval manipulation. Nothing too exotic but the third one had some edge cases I wasn't fully prepared for.

Questions Asked (3)

Q1

Given a list of intervals, merge all overlapping ones and return a sorted list of non-overlapping intervals covering the same ranges.

Algorithms & Data Structures
Author's notes

Sort by start, then walk through and merge if the current interval overlaps the last one in your result list.

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AI HintsAI Generated

Suggested Approach

Start by clarifying edge cases like empty input, single interval, and whether intervals are inclusive/exclusive. Then propose sorting intervals by start time and merging in a single pass, explaining the O(n log n) time and O(n) space complexity. Finally, walk through a concrete example to demonstrate correctness and discuss potential optimizations or variations.

Pro tip: Mention that sorting is the key insight because it reduces the problem to a linear scan, and proactively discuss how you'd handle edge cases like adjacent intervals (e.g., [1,2] and [2,3]) depending on whether they should merge.

1. Clarify requirements and edge cases

Ask about input constraints, interval inclusivity, and expected output format. Confirm handling of empty lists, single intervals, and unsorted input.

2. Outline the algorithm

Explain that you will sort intervals by start time, then iterate and merge overlapping intervals by comparing the current end with the next start.

3. Analyze complexity

State that sorting dominates at O(n log n) time, and the merge pass is O(n), resulting in O(n log n) overall. Space is O(n) for the output (or O(1) extra if merging in-place).

4. Walk through an example

Use a small example like [[1,3],[2,6],[8,10],[15,18]] to show how the algorithm merges [1,3] and [2,6] into [1,6], and produces the final sorted list.

5. Discuss edge cases and variations

Cover cases like intervals that touch at endpoints, large inputs, and whether to merge adjacent intervals. Mention possible optimizations or alternative approaches if asked.

Key Points to Mention

  • Sorting intervals by start time is crucial for efficient merging.
  • Merge condition: if current interval's start <= last merged interval's end, they overlap.
  • Time complexity: O(n log n) due to sorting; space complexity: O(n) for output.
  • Edge cases: empty input, single interval, intervals with same start, adjacent intervals.
  • Inclusive vs exclusive endpoints and how that affects merging.
  • Stability of sorting and potential use of in-place merging to save space.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q2

Repeatedly remove adjacent pairs of identical characters from a string until no more pairs remain. What is the final string?

Algorithms & Data Structures
Author's notes

Stack approach works cleanly here.

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AI HintsAI Generated

Suggested Approach

Clarify the problem by walking through a small example to confirm understanding, then propose an efficient stack-based solution that processes the string in a single pass. Explain the algorithm, analyze its time and space complexity, and discuss edge cases and potential optimizations.

Pro tip: Mention that this is essentially the same as matching parentheses or evaluating expressions, and that a stack naturally handles the 'repeatedly remove' requirement in O(n) time. Also, note that the final string is unique regardless of removal order, which shows deeper insight.

1. Clarify the problem

Restate the problem in your own words and walk through a simple example like 'abba' to confirm that removals can cascade. Ask if the input is ASCII or Unicode, and if the string can be empty.

2. Propose a naive approach

Describe a brute-force method that repeatedly scans the string and removes adjacent pairs until no more exist. Mention its O(n^2) time complexity due to repeated passes.

3. Optimize with a stack

Explain that a stack can process the string in one pass: for each character, if it matches the top of the stack, pop; otherwise, push. This yields O(n) time and O(n) space.

4. Analyze complexity and edge cases

State the time and space complexity of the stack approach. Discuss edge cases: empty string, no pairs, all pairs, and strings with odd length. Mention that the result is independent of removal order.

5. Discuss extensions and optimizations

If asked, mention that the stack can be simulated with a string builder for O(1) space in some languages, or that the problem can be solved in-place with two pointers. Also, note that the final string is unique.

Key Points to Mention

  • Stack data structure for O(n) time complexity
  • Single-pass algorithm vs. repeated scanning
  • Time and space complexity analysis (O(n) time, O(n) space)
  • Edge cases: empty string, no adjacent pairs, all characters paired
  • Uniqueness of the final result regardless of removal order
  • Connection to similar problems like valid parentheses or expression evaluation

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.

Q3

Given a string and an integer k, repeatedly remove any k consecutive identical characters until no such group exists. Return the final string.

Algorithms & Data Structures
Author's notes

This is the harder version of the previous question and I underestimated it at first.

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AI HintsAI Generated

Suggested Approach

Use a stack to process characters one by one, tracking consecutive counts. When the count reaches k, pop the group and merge with the previous stack top if it has the same character, repeating until stable. This yields O(n) time and O(n) space.

Pro tip: Mention that a naive recursive string replacement is O(n^2) or worse, and that the stack approach handles cascading removals in a single pass. Also note edge cases like k=1 (empty string) and k > string length.

1. Clarify and restate

Confirm understanding: remove exactly k consecutive identical characters repeatedly until no such group exists. Ask about constraints (string length, character set) and edge cases (k=1, k > length).

2. Discuss naive approach

Describe a straightforward method: scan for k identical characters, remove them, and repeat until no changes. Note its inefficiency due to repeated scans and string rebuilding.

3. Propose optimal stack solution

Explain using a stack of (character, count) pairs. For each character, increment count if it matches the top; otherwise push new. When count reaches k, pop the group and merge with the new top if same character.

4. Walk through example

Trace the algorithm on a sample like 'deeedbbcccbdaa', k=3 to demonstrate cascading removals and correctness.

5. Analyze complexity and edge cases

State O(n) time and O(n) space. Discuss edge cases: k=1 returns empty string, k > n returns original string, and all characters removed.

Key Points to Mention

  • Stack of (character, count) pairs to track consecutive duplicates
  • Cascading removals handled by merging with previous stack top after popping
  • Time complexity O(n) and space complexity O(n)
  • Edge cases: k=1, k > string length, empty string, no removals
  • Comparison with naive O(n^2) approach and why stack is better
  • Correctness argument: invariant that stack contains no k consecutive identical characters

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.