Course overviewTopic 54 / 152
Algorithms • Topic 08 35 min Linked List

LRU Cache

This topic is a practice problem inside the Linked List module. The goal is not to memorize the title: reconstruct the problem it solves, the mechanism that makes it work, and the signal that tells you when to use it.

LEARNING LOOPWatch→Read→Inspect→Retrieve→Teach back
LRU Cache
Week 5–6 · Topic 54 / 152
Article companion· Week 5–6

This topic is a practice problem inside the Linked List module. The goal is not to memorize the title: reconstruct the problem it solves, the mechanism that makes it work, and the signal that tells you when to use it.

01

What problem does this solve?

Start from the engineering problem rather than the definition. LRU Cache exists because a system needs a reliable way to handle a recurring constraint inside Linked List. Ask what would become slow, ambiguous, unsafe, or impossible without it.

02

How the mechanism works

Break the idea into observable steps. The useful mental model is: input → transformation → decision or state change → output. Keep each step small enough that you can redraw it from memory. The surrounding module is the context: Dummy nodes kill edge cases; fast & slow pointers find middles and cycles.

03

When to reach for it

Use nearby concepts as contrasts. In this module, compare LRU Cache with Linked List mechanics: dummy nodes, runner technique, Reverse Linked List, Merge Two Sorted Lists. The distinction matters because good engineering choices depend on the constraints, not on memorizing isolated definitions.

DUAL CODING

See the mechanism before you memorize it

One diagram, one causal story, one reconstruction task.

VISUAL RECONSTRUCTION

LRU Cache — causal map

4 stages
01

Frame

State the problem and the constraints before naming the technique.

02

Transform

Apply the core mechanism of LRU Cache and track what state changes.

03

Observe

Inspect the artifact, output, invariant, or behavior produced by the mechanism.

04

Transfer

Explain where the same idea appears elsewhere in DSA Patterns.

Trace the mechanism from left to right. On smaller screens, follow the numbered sequence. Then redraw the same flow without looking.
ACTIVE RECONSTRUCTION

Draw the idea yourself

Rebuild the core flow on a real canvas before moving to the worked walkthrough.

SKETCHFLOW

LRU Cache — practice canvas

Sketch the LRU Cache mechanism from memory. Label the input, transformation, observation, and transfer.

Practice canvas ready

The canvas loads when you reach this section.

Draw first. Compare second.Touch + mouse friendly
STEP BY STEP

Walk the system

01

Frame

State the problem and the constraints before naming the technique.

02

Transform

Apply the core mechanism of LRU Cache and track what state changes.

03

Observe

Inspect the artifact, output, invariant, or behavior produced by the mechanism.

04

Transfer

Explain where the same idea appears elsewhere in DSA Patterns.

CONCRETE ARTIFACT

Reconstruction card

Use the card as a generative note, not a summary to copy. Fill it from memory after the explanation.

textcopy → rebuild → modify
TOPIC: LRU Cache
MODULE: Linked List
TYPE: practice problem

PROMPT
What problem does it solve?
What changes step by step?
What evidence proves it worked?
When would you choose something else?
MISCONCEPTIONS

What usually goes wrong

Memorizing LRU Cache without naming the problem it solves.

Skipping the mechanism and jumping from definition straight to the answer.

Confusing a familiar example with the general rule.

Treating a classroom simplification as a universal production rule.

RETRIEVAL PRACTICE

Close the tab. Rebuild it from memory.

Read the question, answer aloud, then reveal.

What problem is LRU Cache designed to solve?Reveal answer

It addresses a recurring constraint inside Linked List. A strong answer names the input, the core mechanism, and the result rather than repeating the title.

What are the four stages of the mental model?Reveal answer

Frame the problem → transform the input/state → observe the evidence → transfer the idea to a new scenario.

Remove Nth From End in one pass — the trick?Reveal answer

Two pointers n+1 apart; when the front hits null, the back sits on the node before the target.

LRU Cache: which two structures combine and why?Reveal answer

Hash map for O(1) lookup + doubly linked list for O(1) move-to-front and evict-from-back.

FEYNMAN

Teach it back in plain English

Explain Floyd's cycle detection as two runners on a circular track.

EXAM / INTERVIEW

What a strong answer sounds like

A strong exam or interview answer should connect purpose → mechanism → example → limitation. For LRU Cache, be ready to reconstruct the process without notes and distinguish it from a nearby concept.

NEXT CONNECTION

Make this idea travel.

Connect it next to: Why pattern-based learning beats grinding • Set up your mistakes log + template notebook • Your spaced revision calendar (Day 1 / 3 / 7 / 21) • Big-O intuition builder: visualize growth rates.

COURSE CONTENTS

LRU Cache

01How This Journey WorksDay 0 · 4 topics0/4
02Complexity, Arrays & HashingWeek 1–2 · 11 topics0/11
03Two PointersWeek 2–3 · 7 topics0/7
04Sliding WindowWeek 3–4 · 8 topics0/8
05StackWeek 4 · 8 topics0/8
06Binary SearchWeek 5 · 8 topics0/8
07Linked ListWeek 5–6 · 10 topics0/10
08TreesWeek 6–7 · 13 topics0/13
09TriesWeek 7 · 4 topics0/4
10Heap / Priority QueueWeek 8 · 8 topics0/8
11BacktrackingWeek 8–9 · 11 topics0/11
12GraphsWeek 9–10 · 17 topics0/17
131-D Dynamic ProgrammingWeek 10–11 · 14 topics0/14
142-D Dynamic ProgrammingWeek 11–12 · 11 topics0/11
15Greedy, Intervals & BitsWeek 12 · 12 topics0/12
16Mock Interviews & Mixed RevisionWeek 13 · 6 topics0/6