← Instacart Interview Insights

Instacart·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
May 2026

Summary

Interviewed for a software engineer role at Instacart. Two coding problems back to back, one systems-flavored and one pure algorithm. Nothing too wild but the combo felt deliberate.

Questions Asked (2)

Q1

You have a very large password file. Write a program that reads only the required password(s) from it while keeping memory usage as low as possible. How do you ensure only the necessary data is loaded into memory?

Algorithms & Data StructuresTechnical Trade-offsSystem Design
Author's notes

My first instinct was to just read the whole file and filter in memory, which is exactly the wrong answer.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying the file format and whether passwords are stored in plaintext or hashed. Then propose a streaming approach that reads the file line by line, comparing each line to the target username(s) without loading the entire file. Emphasize constant memory usage and discuss trade-offs between memory and speed.

Pro tip: Mention that if the file is sorted by username, you can use binary search to jump directly to the relevant section, but be prepared to discuss the overhead of seeking in large files. Also, consider using memory-mapped files for efficient random access without loading everything into memory.

1. Clarify requirements and constraints

Ask about the file format (e.g., 'username:password' per line), size, whether it's sorted, and if multiple passwords need to be retrieved. Confirm that memory usage is the primary concern.

2. Choose a streaming approach

Propose reading the file line by line using a buffered reader, which keeps memory usage constant regardless of file size. For each line, parse and check if it matches the target username(s).

3. Optimize for multiple lookups

If multiple passwords are needed, consider building an index (e.g., username to file offset) in a separate pass, or if the file is sorted, use binary search to locate entries efficiently.

4. Handle edge cases and performance

Discuss handling of large lines, encoding, and I/O bottlenecks. Mention that streaming may be slower than loading into memory, but it's necessary for low memory.

5. Summarize trade-offs

Conclude by comparing streaming vs. indexing vs. memory-mapping, highlighting that streaming is simplest and uses minimal memory, while indexing trades memory for speed.

Key Points to Mention

  • Streaming with buffered reader to keep memory O(1)
  • Line-by-line parsing and comparison
  • Binary search if file is sorted by username
  • Building an index (username -> offset) for multiple lookups
  • Memory-mapped files for efficient random access
  • Trade-offs between memory usage and speed

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

Q2

Given a mathematical expression as a string, implement a program to evaluate it using a depth-first search approach.

Algorithms & Data Structures
Author's notes

Classic expression parsing problem but the DFS framing threw me a little.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Clarify the expression grammar (operators, parentheses, precedence) and then design a recursive descent parser that evaluates the expression using DFS. Implement the parser with functions for each precedence level, handling parentheses recursively, and test with edge cases.

Pro tip: Mention that while DFS (recursive descent) is natural for expression evaluation, you should be mindful of recursion depth for deeply nested expressions and consider an iterative approach if needed. Also, discuss how to handle unary operators and operator associativity.

1. Clarify requirements and grammar

Ask about supported operators, precedence, associativity, parentheses, and number formats. Define the grammar (e.g., expression -> term (+|- term)*, term -> factor (*|/ factor)*, factor -> number | '(' expression ')').

2. Design recursive descent parser

Create functions for each grammar rule (parseExpression, parseTerm, parseFactor) that recursively evaluate subexpressions. Use DFS to traverse the expression tree implicitly.

3. Implement evaluation logic

In each function, parse tokens, apply operators with correct precedence, and combine results. Handle parentheses by recursively calling parseExpression.

4. Handle edge cases and errors

Consider unary minus, division by zero, invalid characters, and mismatched parentheses. Add error handling and validation.

5. Test and optimize

Test with various expressions, including nested parentheses and multiple operators. Discuss time/space complexity (O(n) time, O(d) space for recursion depth d).

Key Points to Mention

  • Operator precedence and associativity rules (e.g., * and / before + and -; left associativity).
  • Recursive descent parsing as a form of DFS, with functions for each precedence level.
  • Handling parentheses by recursively evaluating the subexpression inside.
  • Tokenization: splitting the string into numbers, operators, and parentheses.
  • Error handling for invalid input, division by zero, and unbalanced parentheses.
  • Time and space complexity: O(n) time, O(d) space where d is nesting depth.

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