Meta·Software Engineer·Onsite - Coding / Algorithms·Senior

SeniorPrefer not to say

Apr 2026Remote

Summary

Meta SWE coding round with a deliberately underspecified compiler IR problem where the whole trick is that the cost constants aren't in the prompt, they're buried in the unit test assertions. Felt like a puzzle more than a coding problem, and apparently at least one person's AI model crashed mid-session which sounds like a nightmare.

Questions Asked (1)

Implement a function `extract_time_and_mem_cost(instruction_file)` that parses a toy compiler IR file of straight-line three-address code and returns the total time and memory cost. The per-operator costs are not given anywhere in the prompt.

Algorithms & Data StructuresAdaptability & AmbiguityTechnical Trade-offs

Author's notes

The thing that trips people up is spending the first 20 minutes asking the interviewer what each operator costs, and the interviewer just kind of...

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AI HintsAI Generated

Suggested Approach

First, clarify the ambiguity around per-operator costs by proposing a reasonable default cost model (e.g., each operator costs 1 time unit and 1 memory unit) and state that the solution can be parameterized. Then, design a parser that reads the IR file line by line, extracts the opcode and operands, and accumulates the total time and memory costs using a dictionary mapping opcodes to their costs. Finally, discuss how to handle edge cases like comments, blank lines, and different instruction formats.

Pro tip: Demonstrate adaptability by explicitly calling out the missing cost information and offering to make the cost model configurable, showing you can handle ambiguity while still delivering a working solution.

1. Clarify requirements and assumptions

Ask or state assumptions about the IR format, the set of operators, and the missing per-operator costs. Propose a default cost model (e.g., uniform cost per operator) and note that it can be adjusted.

2. Design the parser

Outline a line-by-line parsing strategy: skip comments and blank lines, tokenize each instruction to extract the opcode and operands, and handle potential variations in syntax.

3. Define cost accumulation

Create a cost table (dictionary) mapping each opcode to its time and memory cost. For each parsed instruction, look up the opcode and add its costs to running totals.

4. Handle edge cases and errors

Consider malformed lines, unknown opcodes, and empty files. Decide whether to raise exceptions, log warnings, or use default costs for unknown opcodes.

5. Return and discuss results

Return the total time and memory cost as a tuple or dictionary. Discuss potential extensions like configurable cost models or support for more complex IR.

Key Points to Mention

Ambiguity handling: explicitly address the missing per-operator costs and propose a reasonable default or configurable model.
Parsing strategy: line-by-line processing with tokenization, skipping comments and blank lines.
Cost model: use a dictionary mapping opcodes to time and memory costs, with a default for unknown opcodes.
Edge cases: empty file, malformed lines, unknown opcodes, and how to handle them gracefully.
Extensibility: design the function to accept an optional cost model parameter for flexibility.
Complexity: linear time in the number of instructions, O(1) extra space for totals and cost table.

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