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Snowflake·Software Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Snowflake software engineer interview with a meaty expression evaluator problem. The follow-ups kept coming and I wasn't totally ready for all of them.

Questions Asked (3)

Q1

Build an expression evaluator that handles non-negative integers, named variables (resolved from a dictionary), the four arithmetic operators, parentheses, and spaces. It needs to respect standard precedence and left-to-right associativity, handle unary plus and minus, truncate division toward zero, run in O(L) time and space, and return an error on bad tokens or mismatched parentheses.

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

This is basically a full recursive-descent or shunting-yard parser and I went with the recursive descent approach since I find it easier to reason about precedence that way.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then propose a two-stack or recursive descent parser that tokenizes the input and evaluates expressions respecting precedence and associativity. Emphasize linear time and space complexity, and discuss error handling for invalid tokens and mismatched parentheses.

Pro tip: Mention that you would write unit tests for edge cases like unary operators, division truncation, and nested parentheses before coding, and discuss how to extend the evaluator to support more operators or functions.

1. Clarify requirements and edge cases

Ask about variable resolution, error handling, and expected input size to confirm O(L) constraints. Discuss edge cases like unary plus/minus, division truncation, and empty input.

2. Choose parsing strategy

Decide between recursive descent and two-stack (shunting-yard) approach. Explain why either can achieve O(L) time and space with proper implementation.

3. Outline tokenization and evaluation

Describe how to tokenize the input (numbers, variables, operators, parentheses) and evaluate using precedence and associativity rules. Mention handling unary operators by tracking context.

4. Address error handling and complexity

Explain how to detect invalid tokens and mismatched parentheses, and return errors. Confirm that the algorithm runs in O(L) time and space.

5. Discuss testing and extensions

Propose test cases for edge conditions and suggest how to extend the evaluator for additional features like exponentiation or functions.

Key Points to Mention

  • Tokenization: identify numbers, variables, operators, and parentheses, skipping spaces.
  • Precedence and associativity: use a stack or recursive descent to enforce standard rules.
  • Unary operators: handle unary plus/minus by tracking whether an operator is expected.
  • Division truncation: implement integer division that truncates toward zero (e.g., using int() in Python or trunc() in C++).
  • Error handling: return errors for invalid tokens, undefined variables, and mismatched parentheses.
  • Complexity: ensure O(L) time and space by processing each character once and using stacks of bounded size.

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

Q2

Extend the evaluator to support exponentiation using '^', which is right-associative. How does that change your implementation?

Algorithms & Data StructuresTechnical Trade-offs
Author's notes

Right-associativity is the interesting wrinkle here.

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AI HintsAI Generated

Suggested Approach

First, explain how the existing evaluator works (e.g., recursive descent or shunting-yard) and where '^' fits in the precedence hierarchy. Then, detail the specific changes needed to make '^' right-associative, such as adjusting the parsing loop or operator stack handling. Finally, discuss trade-offs and edge cases like unary minus and associativity interactions.

Pro tip: Mention that right-associativity can be implemented by recursing on the right-hand side instead of looping, and highlight that this avoids stack overflow for deeply nested exponents. Also, note that many languages give '^' higher precedence than unary minus, so clarify your choice.

1. Review existing evaluator structure

Briefly describe the current parsing/evaluation method (e.g., recursive descent, shunting-yard) and how binary operators are handled. Identify where precedence and associativity are enforced.

2. Define precedence and associativity of '^'

State that '^' has higher precedence than multiplicative operators and is right-associative. Discuss how this affects the grammar or operator table.

3. Modify parsing logic for right-associativity

For recursive descent, change the right-hand side to call the exponentiation rule recursively (e.g., parseExponent -> parseUnary ('^' parseExponent)?). For shunting-yard, adjust the stack handling to pop only when precedence is strictly greater.

4. Handle edge cases and interactions

Address unary minus (e.g., -2^2 should be -(2^2) if '^' has higher precedence), multiple exponents (2^3^2 = 2^(3^2)), and potential stack overflow with deep recursion.

5. Discuss trade-offs and testing

Compare recursive vs. iterative approaches, mention performance implications, and outline test cases to verify correctness (e.g., 2^3^2, 2^-3, -2^2).

Key Points to Mention

  • Precedence of '^' relative to other operators (higher than * and /, lower than parentheses and unary operators depending on language).
  • Right-associativity: a^b^c = a^(b^c), implemented via recursion or stack condition (pop only if precedence > current).
  • Interaction with unary minus: typically -2^2 = -(2^2) = -4, not (-2)^2 = 4.
  • Recursive descent: change the right-hand side of the exponentiation rule to call itself recursively.
  • Shunting-yard: when encountering '^', pop operators with higher precedence (not equal) to achieve right-associativity.
  • Edge cases: negative exponents, zero exponent, deeply nested exponents causing stack overflow, and floating-point precision.

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

Q3

Further extend the evaluator to support a built-in two-argument function like max(a, b). How would you handle function calls in the grammar?

Algorithms & Data StructuresSystem Design
Author's notes

Didn't see this one coming as a follow-up to the follow-up.

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AI HintsAI Generated

Suggested Approach

Start by explaining how to extend the grammar to recognize function calls with a name and parenthesized argument list, then discuss the AST representation and evaluation strategy. Emphasize that the evaluator needs to dispatch to built-in functions like max, handling arity and type checking.

Pro tip: Mention that you would separate parsing from evaluation and use a function registry to easily add more built-in functions later, showing foresight for extensibility.

1. Extend the grammar

Add a production rule for function calls, e.g., primary -> IDENTIFIER '(' expression (',' expression)* ')'. This allows parsing of calls like max(a, b).

2. Update the AST

Introduce a FunctionCall node that stores the function name and a list of argument expressions. This node will be visited during evaluation.

3. Implement evaluation

In the evaluator, when visiting a FunctionCall node, evaluate each argument, then look up the function in a built-in function table and invoke it with the evaluated arguments.

4. Handle built-in functions

Define a mapping from function names to implementations (e.g., max takes two numbers and returns the larger). Include arity and type checks, throwing errors for invalid calls.

5. Test and extend

Write tests for valid and invalid function calls, and ensure the design allows adding more functions easily by extending the function table.

Key Points to Mention

  • Grammar rule for function calls with comma-separated arguments
  • AST node for function calls (name + argument list)
  • Evaluation strategy: evaluate arguments then dispatch to function
  • Built-in function registry for extensibility
  • Arity and type checking for function arguments
  • Error handling for unknown functions or invalid arguments

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