A · Professional problem solving and implementation
Coding and abstraction
Turning a need into correct, readable, evolvable code with fitting abstractions.
Classification boundary
Include: Include implementation, code reading, abstraction, and complexity reasoning.
Choose a neighboring leaf when: Use debugging for diagnosing existing failures and computer science for explaining underlying principles.
This capability may appear in standards across different stages. Explore stage expectations
29 questions
Choose a group based on the evidence you need. Groups follow existing question formats, not difficulty or mandatory prerequisites. Each batch has up to eight questions.
Concepts and boundaries2
Check concepts, assumptions, and conditions of use.
Questions 1–2
- You need a structure that supports fast insert, fast lookup, and ordered iteration. How would you choose among candidates, and what would you give up?
- After a service is registered as a singleton, different user requests occasionally see one another’s temporary state. How would you explain dependency-injection lifetimes and design a safe object boundary?
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Judgment and options10
Compare goals, constraints, options, and trade-offs.
Questions 1–8
- A sign-up form ends up in inconsistent states because of duplicate submissions and weak-network retries. How would you map its states and transitions, and decide which logic to extract into its own unit?
- A user backgrounds the app while editing, and the operating system may kill its process. On return, which state should be restored and which should be reloaded, and how would you avoid losing a draft or overwriting newer data?
- When writing code and reviewing it, what checks have become habit for avoiding performance problems such as querying a database inside a loop or holding large objects too long? How do you know they actually work?
- The framework allows concurrent background UI updates, but a slow response occasionally overwrites a newer selection. How would you design concurrent state updates?
- A complex form has field validation, cross-field rules, and server errors that overwrite one another during edits. How would you divide framework state from business state?
- Several pages share server data and framework caching reduces requests, but stale results appear after users switch accounts. How would you design cache keys and invalidation boundaries?
- A third-party SDK callback updates data, but the UI does not refresh; forcing a refresh causes duplicate updates. How would you identify the framework’s change-detection boundary and choose the right integration point?
- After a list item changes from record A to record B, its input still contains A’s draft. How would you explain component identity, keys, and state reuse, and choose where to fix it?
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Questions 9–10
- A custom dialog works with a mouse, but keyboard users cannot reliably enter, close, or return from it. Which focus-management behaviors would you inspect, and how would you verify a fix?
- Several product teams override shared component styles with CSS, causing frequent regressions after upgrades. How would you choose between adding configuration, splitting the component, or keeping exceptions?
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Implementation and verification17
Examine execution, verification, and correction.
Questions 1–8
- How do you usually handle null values, empty strings, out-of-range access, and invalid input when writing code? Tell me about a time a missing up-front check caused a problem in testing or production, and what habit changed as a result.
- Implement a small cache that evicts the least recently used entry when full. What time cost does each operation need, and which tests do you write first?
- Implement a retry wrapper that retries by error type, supports a maximum attempt count, backoff, and cancellation, and does not overwhelm the dependency. Define the interface before coding, then explain how to make clocks, waits, and tests deterministic.
- A very large CSV must be validated without loading the whole file into memory. On malformed rows, the tool should report line numbers and continue checking. How would you design the parser interface?
- Implement a map with concurrent reads and writes, per-entry expiration, and expired-entry cleanup. How would you define expiration semantics, synchronization boundaries, and deterministic tests?
- Implement deep equality for inputs that may contain nested arrays, shared references, and cycles. Define equality semantics first, then avoid infinite recursion and accidental confusion of reference structures.
- Implement a small task queue with concurrent workers, cancellation, and retries; tests must not depend on real sleeps. How would you design the scheduling interface and state transitions?
- Implement an incremental UTF-8 log parser that receives chunks which may split multibyte characters, reorder fields, contain multiple records, or include an exceptionally long line. Define parser state, error recovery, and memory limits, then implement repeatable core logic.
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Questions 9–16
- Design a reusable virtualized list: it renders only visible rows, but selection state must not leak to different data when DOM nodes are recycled. How would you define the interface and test it?
- Given a set of records that may exceed memory capacity, process them in batches while allowing the caller to cancel. Describe or implement an interface that bounds memory, locates errors, and starts no new batch after cancellation.
- Several callers read a configuration file whose fields keep growing; older fields may be absent, and new versions must allow unknown extension fields. How would you design a parsing interface so callers can understand defaults, validation errors, and backward-compatibility behavior?
- The input contains time intervals that may overlap or touch, and callers need to find records covering a given instant. Describe or implement a merge and query strategy, including whether endpoints are inclusive.
- An API adds a new state, but older clients may not recognize it; some must still display the record, while critical operations must reject unknown states. How would you design parsing and defaults so an unknown value is not mistaken for a valid state?
- Events arrive as a stream, and some duplicates may be hours apart. Memory must remain bounded, and deduplication must survive process restarts. How would you define the time window, persistent state, and false-positive boundaries?
- Given many timestamped records, return the top K by score and preserve earlier items on ties. How would you implement it and analyze edge cases?
- Several sources are individually time-sorted, but total data exceeds memory. Explain how to merge output and handle a source that slows or disconnects temporarily.
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Questions 17–17
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