← Jane Street Interview Insights
The reference was basically a standard phone calculator and my first instinct was to just start banging out HTML.
Start by clarifying requirements and constraints with the interviewer, then outline a component-based architecture and state management plan before coding. Focus on matching the reference app's visual style and core functionality, while discussing trade-offs and potential edge cases.
Pro tip: Demonstrate your thought process by narrating your decisions and asking clarifying questions; interviewers value how you approach problems and communicate more than just getting a working solution.
Ask about the reference app's specific features, expected input methods, and any constraints (e.g., browser support, performance). Confirm the scope and priorities.
Outline a component structure (e.g., display, buttons, logic) and decide on state management (e.g., React state, Redux). Consider separation of concerns and reusability.
Build the calculator's arithmetic operations and input handling, ensuring correct order of operations and error handling (e.g., division by zero).
Replicate the reference app's layout, colors, typography, and button styles using CSS. Pay attention to responsive design and accessibility.
Manually test edge cases and compare with the reference app. Discuss potential improvements or trade-offs made during implementation.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
They asked me to clarify this before coding.
Acknowledge that the choice depends on the calculator's intended use case and user expectations, then propose a hybrid approach or a configurable setting. Emphasize that for a standard calculator, operator precedence is expected, but for a simple four-function calculator, immediate execution may be more intuitive. Finally, discuss how to communicate the behavior to users and handle edge cases.
Pro tip: Mention that many physical calculators have a switch for this exact choice, and that mimicking that physical affordance in software can delight users. Also, note that Jane Street values clear reasoning about trade-offs over picking a 'correct' answer.
Ask clarifying questions about the target users, the calculator's complexity, and whether it's for basic arithmetic or scientific use. This shows you don't jump to solutions without understanding requirements.
Discuss pros and cons of each approach: immediate execution is simpler and matches many physical calculators, while operator precedence aligns with mathematical convention and user expectations from programming languages.
Suggest a hybrid approach: default to operator precedence for a standard calculator, but offer a mode toggle for immediate execution. Alternatively, if the calculator is extremely simple, immediate execution might be acceptable.
Explain how you would implement the chosen approach (e.g., using a parser or a simple stack) and how you would make the behavior clear to users (e.g., visual cues, documentation).
Reiterate that the decision should be driven by user needs and product goals, and that you would validate the choice through user testing or feedback.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by outlining a layered accessibility strategy: semantic HTML foundation, full keyboard operability, robust focus management, and live region announcements. Then discuss specific implementation details and trade-offs, such as roving tabindex for keypad navigation and aria-live for result updates. Emphasize testing with screen readers and keyboard-only navigation to ensure a seamless experience.
Pro tip: Demonstrate awareness that screen reader users often prefer a single tab stop for the calculator with arrow-key navigation inside, rather than tabbing through every button—this shows you understand real-world AT usage patterns.
Use native <button> elements for keys and appropriate ARIA roles (e.g., role='application' or 'group') to define the calculator's structure. Ensure labels and instructions are programmatically associated.
Implement full keyboard support: Tab to focus the calculator, arrow keys to navigate between buttons (roving tabindex), Enter/Space to activate, and shortcuts for common operations (e.g., 'c' for clear).
Manage focus dynamically: after an operation, keep focus on the activated button or move it logically (e.g., to the result display). Use focus trapping if the calculator is in a modal, and restore focus when closed.
Use an aria-live region (polite or assertive) to announce results and errors. Ensure announcements are concise and not overly verbose, and avoid double-speaking by hiding redundant visual updates from AT.
Test with keyboard only and screen readers (NVDA, VoiceOver). Validate with automated tools (axe) and manual checks. Iterate based on feedback to handle edge cases like rapid input.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Basically asking if I know how to write a parser.
Start by clarifying the current calculator engine's architecture and constraints, then propose a two-phase approach: tokenization followed by parsing using a precedence-aware algorithm like shunting-yard or recursive descent. Emphasize how this integrates with the existing engine, including evaluation and error handling.
Pro tip: Mention that you'd build a tokenizer and parser as separate, testable modules, and discuss how to handle edge cases like unary minus and implicit multiplication. This shows you think about maintainability and robustness, which Jane Street values.
Ask about the current engine's design, supported operations, and any performance or UI constraints. Confirm whether the extension should be incremental or a rewrite.
Break the input string into tokens (numbers, operators, parentheses) and handle edge cases like multi-digit numbers and unary operators.
Select an algorithm that respects operator precedence and parentheses, such as shunting-yard (iterative) or recursive descent (recursive). Explain the trade-offs.
Evaluate the parsed expression, either directly during parsing (e.g., recursive descent) or by converting to an AST or RPN and then evaluating.
Integrate the new parser with the existing calculator engine, ensuring backward compatibility. Write unit tests for precedence, parentheses, and error cases.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
This one I actually liked because separating the engine into a pure function made it easy to answer.
Start by clarifying the calculator's scope and interface, then outline a layered testing strategy from pure functions to integration. Prioritize test sequences based on risk and business impact, explaining your reasoning for each choice.
Pro tip: Emphasize property-based testing for arithmetic invariants (e.g., commutativity, associativity) and discuss how you'd handle floating-point precision—this shows depth beyond basic unit tests.
Ask about the calculator's features (operations, memory, error handling) and its API to define testable units. This ensures your tests target the right behavior.
Break down the calculator into pure functions (e.g., add, subtract) and stateful components (e.g., display, memory). Note external dependencies like UI or I/O that need mocking.
List test cases covering normal, edge, and error scenarios. Prioritize based on risk: core arithmetic, boundary conditions (overflow, division by zero), and user-critical flows.
Select appropriate techniques: example-based tests for specific cases, property-based tests for invariants, and mocks for dependencies. Mention tools like Jest, Mocha, or fast-check.
Justify your test sequence by linking to business impact, likelihood of failure, and cost of bugs. For example, test basic operations first as they are most used.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by explaining why floating-point precision issues occur (IEEE 754 binary representation), then discuss practical strategies for handling display issues in frontend applications, such as using toFixed, toPrecision, or libraries like decimal.js. Emphasize that the choice depends on the context: for display, rounding is often sufficient, but for financial calculations, exact decimal arithmetic is necessary.
Pro tip: Mention that while rounding for display is common, it's crucial to avoid accumulating errors in calculations by using integer arithmetic (e.g., cents) or a decimal library, and always be explicit about the trade-offs between performance and precision.
Briefly explain that floating-point numbers are represented in binary and cannot exactly represent many decimal fractions, leading to tiny errors.
Clarify that the issue often only matters for display; for internal calculations, you might need exact arithmetic. Discuss the importance of not using floating-point for critical calculations like money.
Describe common techniques: using toFixed() for rounding to a fixed number of decimals, toPrecision() for significant digits, or Intl.NumberFormat for locale-aware formatting.
Mention alternatives like using integer arithmetic (e.g., working in cents), or libraries like decimal.js, big.js, or bignumber.js for arbitrary-precision decimal math.
Summarize that the choice depends on requirements: performance vs. precision, and recommend being consistent and documenting the approach.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.