Instacart·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026

Summary

Coding round at Instacart for a software engineer role. The problem looked like a simple variable evaluation exercise until the recursive references showed up and things got messier fast.

Questions Asked (1)

You're given a target variable and a list of assignment strings like 'Ti = expression', where each expression is a number, a single variable, or simple arithmetic over variables and numbers. Compute the numeric value of the target variable. Then extend the solution to handle recursive variable references, and detect cycles or unresolvable references.

Algorithms & Data StructuresTechnical Trade-offs

Author's notes

Started fine with the base case, just parse the string and evaluate.

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AI HintsAI Generated

Suggested Approach

Model the assignments as a directed graph where each variable points to its dependencies, then use DFS with memoization to compute values while tracking the recursion stack to detect cycles. Discuss trade-offs between iterative topological sort and recursive DFS, and handle edge cases like missing variables and invalid expressions.

Pro tip: Explicitly separate parsing, dependency resolution, and evaluation phases; this modularity makes it easy to extend to cycles and unresolvable references. Also, mention that memoization avoids redundant computation and that cycle detection can be done with a 'visiting' state in DFS.

1. Parse and Build Dependency Graph

Parse each assignment string into a variable and an expression, then extract all variable references from the expression to build a directed graph of dependencies.

2. Design Evaluation Strategy

Choose between recursive DFS with memoization or iterative topological sort. Explain why DFS naturally handles cycles via a recursion stack, while topological sort requires explicit cycle detection.

3. Implement Evaluation with Cycle Detection

For DFS, maintain states (unvisited, visiting, visited) to detect cycles. When a variable is needed, recursively evaluate its dependencies; if a cycle is found, raise an error or return a sentinel.

4. Handle Edge Cases and Errors

Detect unresolvable references (variables not defined in any assignment) and invalid expressions (e.g., division by zero, syntax errors). Decide on error handling: throw exceptions or return error codes.

5. Analyze Complexity and Trade-offs

Discuss time and space complexity: O(V+E) for graph traversal, with memoization reducing repeated work. Compare recursive vs iterative approaches in terms of stack depth, readability, and cycle detection ease.

Key Points to Mention

Graph representation: adjacency list mapping each variable to its dependencies.
Cycle detection using DFS with a recursion stack or three-color marking (white, gray, black).
Memoization to cache computed values and avoid redundant evaluations.
Handling unresolvable references: variables not defined in any assignment should raise an error.
Expression parsing: tokenize and evaluate arithmetic operations, ensuring correct operator precedence.
Trade-offs: recursive DFS is simpler but may hit recursion limits; iterative topological sort is more robust for large graphs.

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