The Runtime Theory
medium · 3h · 11 steps

Algorithmic Problem Solving

Build a repeatable method for analyzing, selecting, and proving algorithms across arrays, windows, and graphs.

Curriculum (11 steps)

1

An analysis begins by naming the input size and the operation whose growth matters.

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2

Search and sorting choices depend on what is already known about the data and what operations the product needs.

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3

Return the index of target in a sorted array, or -1 when it is absent.

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4

Two Sum

practice

Return the indices of two distinct values whose sum equals the target.

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5

3Sum

practice

Return unique triples whose values sum to zero; input indices do not matter.

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6

A graph models entities as vertices and relationships as edges.

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7

An interactive concept flow for representing a graph before traversing it, from its assumptions through the main operation and boundary checks.

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8

Follow the key state changes and boundary checks involved in representing a graph before traversing it.

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9

Count connected land regions in a grid where horizontal and vertical neighbors connect.

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10

Determine whether every course can be completed given prerequisite dependencies.

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11

Explain the model, execution steps, complexity, and limits of representing a graph before traversing it.

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