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752 matching entries · page 1 of 16

Programming · Hard

Dijkstra's Algorithm #1

Supported standard problem · Match confidence: high

Optiver · Topic guidanceCitadel · Topic guidanceCitadel Securities · Topic guidanceHudson River Trading · Topic guidance
About this question’s source match

The title and Programming / Graphs classification fit the linked public problem. This entry uses an independently worded practice statement and original implementation. This public catalogue example was read directly. The private numbered sequel is not inferred from it.

Implement solve(graph,start,end), returning a minimum-weight directed path as a list of node labels, or None if unreachable. graph maps each string label to a dictionary of outgoing neighbor:positive_integer_weight pairs. If start=end, return [start]. Any shortest path is acceptable.

Assumptions and constraints

  • Every endpoint is a key in graph; start and end exist.
  • Weights are positive integers.
  • <= 100000 vertices; <= 500000 edges

Examples

graph={"s":{"a":2,"t":8},"a":{"t":3},"t":{}}, start="s", end="t"
→ [
  "s",
  "a",
  "t"
]

The path through a costs 5 rather than 8.

Company preparation relevance

These links connect this exercise to companies’ public examples or stated interview topics. They do not establish that a company asked this exact Learnr question.

  • Optiver

    Official topic guidance

    Topic overlap: shortest paths “Dijkstra's Algorithm #1” and streaming medians “Streaming Median” offer concrete time/space complexity and design-tradeoff practice matching the guide’s core-algorithm and performance preparation topics.

    Optiver interview tips for Software Engineers ↗
    Evidence scope and uncertainty

    Specific algorithms selected by Learnr; the official page does not say these named algorithms or titles are asked.

    These are Learnr-authored exercises selected for topic overlap. The company does not name these catalogue titles or verify that these exact questions were asked.

  • Citadel

    Official topic guidance

    Topic overlap: pair searching “All Pairs”, graph shortest paths “Dijkstra's Algorithm #1”, linked-list cycles “Linked List Cycle” and heaps “Priority Queue Using Heaps” provide coding/data-structure/algorithm practice matching the stated campus research interview focus.

    Our Campus Quantitative Research Interview Process ↗
    Evidence scope and uncertainty

    Official guide dated 9 November 2024; explicitly describes Citadel and Citadel Securities together. Role/date specific; no present universal timing asserted.

    These are Learnr-authored exercises selected for topic overlap. The company does not name these catalogue titles or verify that these exact questions were asked.

  • Citadel Securities

    Official topic guidance

    Topic overlap: pair search “All Pairs”, shortest paths “Dijkstra's Algorithm #1”, linked lists “Linked List Cycle”, heaps “Priority Queue Using Heaps” and streaming median “Streaming Median” exercise programming, data structures and algorithms. The official guide explicitly covers both Citadel and Citadel Securities.

    Our Campus Quantitative Research Interview Process ↗
    Evidence scope and uncertainty

    Shared campus quantitative research guide dated 9 November 2024. This does not transfer every Citadel job requirement to Citadel Securities or establish an engineering-specific process.

    These are Learnr-authored exercises selected for topic overlap. The company does not name these catalogue titles or verify that these exact questions were asked.

  • Hudson River Trading

    Official topic guidance

    Topic overlap: graph state handling “Dijkstra's Algorithm #1” and heap balancing “Streaming Median” support code design, invariants, complexity and debugging discussions. These are selected fundamentals exercises, not officially named HRT questions.

    Engineering and Interviewing at HRT — Joe Smith ↗
    Evidence scope and uncertainty

    Engineering coding/debugging/design preparation. Does not claim coverage of hardware, operating systems, networking or low-level C++ knowledge, and does not describe Algo/quantitative research interviews.

    These are Learnr-authored exercises selected for topic overlap. The company does not name these catalogue titles or verify that these exact questions were asked.

References

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Catalogue metadata captured 2026-10-12. Metadata source.