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Google·Software Engineer·Technical Phone Screen·Intermediate

IntermediateRejected
Jun 2026

Summary

One round at Google for a software engineer role, a single coding problem that felt like it went well but apparently didn't. Still not sure what I missed.

Questions Asked (1)

Q1

Given a string representing nested math function calls like add(1, sub(1, 0)), write a function to evaluate and return the result.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Went iterative instead of trying to split the string recursively.

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AI HintsAI Generated

Suggested Approach

Clarify the grammar and constraints of the input string, then propose a recursive descent parser that evaluates expressions on the fly. Discuss handling of nested calls, numbers, whitespace, and error cases, and analyze time and space complexity.

Pro tip: Mention that you can avoid building an explicit AST by evaluating during parsing, which reduces memory overhead and simplifies the code. Also, proactively discuss edge cases like negative numbers, multi-digit numbers, and malformed input to show thoroughness.

1. Clarify requirements and constraints

Ask about the allowed function names, number formats (e.g., negative, decimals), whitespace, and error handling expectations. Confirm whether the input is guaranteed valid or if error handling is required.

2. Define the grammar and parsing strategy

Outline a simple grammar: expression = function '(' expression (',' expression)* ')' | number. Choose a recursive descent parser that evaluates as it parses, avoiding an explicit AST.

3. Implement the parser/evaluator

Write a function that scans the string, parses function names, arguments, and numbers, and recursively evaluates sub-expressions. Use an index pointer to track position and handle commas and parentheses.

4. Handle edge cases and errors

Address malformed input, unknown functions, division by zero, and unexpected tokens. Decide whether to throw exceptions or return error codes, and discuss with the interviewer.

5. Analyze complexity and test

State that time complexity is O(n) where n is the string length, and space is O(d) for recursion depth. Walk through examples like 'add(1, sub(1, 0))' and test edge cases.

Key Points to Mention

  • Recursive descent parsing and on-the-fly evaluation
  • Grammar definition and tokenization (numbers, function names, parentheses, commas)
  • Handling nested expressions via recursion
  • Time and space complexity analysis
  • Error handling and input validation
  • Potential optimizations like iterative parsing or memoization (if applicable)

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