Practise Linked Lists, Stacks & Queues one question at a time. Answer out loud or in writing, get graded, and see exactly what you missed.
What is a linked list, and how does it differ from an array?
A linked list chains elements together through nodes. Each node holds a value and a pointer to the next node. The list only knows where its first node lives, so you reach any element by following pointers one hop at a time.
An array stores elements side by side in one contiguous block. That layout lets you jump straight to index 5 by arithmetic. A linked list cannot, so reaching position 5 costs O(n) hops. Arrays give O(1) random access, and linked lists give O(n).
The tradeoff flips for growth. An array has a fixed block, so growing may mean copying everything. A linked list just allocates a node and rewires a pointer. Choose based on whether you index often or reshape often.
Missed:
“A stack is a collection where you can only add or remove items at the top: you push to put something on and pop to take the top item off. LIFO means last in, first out, so the item I added most recently is the first one I get back, like taking the top plate off a pile.”
Knew itThey have push/pop at the top and LIFO nailed with a clean example. Missing the real-world tie-in, like undo history or function calls, that shows why the ordering matters.
Missed: Doesn't mention why this ordering matters in practice, like reversing or backtracking.
Missed: No mention of real applications like browser back buttons, undo, or function calls.
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What it covers
All 78 questions
Linked list basics
What a node, head and tail are, singly, doubly and circular lists and what the back pointer costs, and how access, search and insertion compare with arrays.
- What is a linked list, and how does it differ from an array?
- What is the difference between a singly and a doubly linked list?
- What do insertion and deletion cost in a linked list versus an array?
- When should you use a linked list instead of an array?
- How do you find the Nth element of a linked list, and what does it cost? Pro
- What is a node, and what does each node store in a linked list? Pro
- Why does a linked list keep a head pointer, and when do you add a tail? Pro
- What is a circular linked list, and where is it used? Pro
- Why is random access slow in a linked list compared to an array? Pro
- What does a doubly linked list's extra pointer buy you, and what does it cost? Pro
- How does insertion into a sorted linked list compare to a sorted array? Pro
- Why can't you binary search a linked list efficiently? Pro
Stack and queue basics
LIFO and FIFO, the core operations and their costs, deques and priority queues, and the everyday problems each structure fits.
- What is a stack, and what does LIFO actually mean?
- What is a queue, and what does FIFO actually mean?
- What are the core operations of a stack, and what do they cost?
- What are the core operations of a queue, and what do they cost?
- What is a deque, and what can it do that a stack or queue cannot?
- What everyday problems do stacks naturally solve? Pro
- What everyday problems do queues naturally solve? Pro
- Why are stacks and queues defined by their operations rather than their storage? Pro
- What is the difference between a stack and a queue? Pro
- How does a priority queue differ from a plain FIFO queue? Pro
Building stacks, queues and deques
Backing stacks, queues and deques with arrays, linked lists or ring buffers, amortized growth, and building one structure from another.
- How do you implement a stack, and what data structure backs it?
- How do you implement a queue, and what data structure backs it?
- When would you back a stack with an array versus a linked list? Pro
- When would you back a queue with an array versus a linked list? Pro
- Why does a naive array-backed queue waste space, and how do you fix it? Pro
- What is a ring buffer, and how do its head and tail wrap around? Pro
- How do you implement a deque so both ends stay O(1)? Pro
- How do you build a queue from two stacks, and what does it cost? Pro
- Why is push on a dynamic-array stack O(1) amortized but not worst case? Pro
- How do you implement a stack using queues, and what does it cost? Pro
- How do you implement a stack that returns its minimum in O(1)? Pro
Linked list pointer techniques
Reversal, fast and slow pointers, sentinels, splicing, deleting from a bare pointer, and the edge cases and repairs of doubly linked lists.
- How does a sentinel node remove edge cases from list insertion and deletion? Pro
- How do you detect a cycle in a linked list, and what does the idea cost? Pro
- What is the idea behind reversing a linked list in place, and its cost? Pro
- Why is deleting a node hard when you only have a pointer to it? Pro
- What makes splicing or splitting linked lists cheap? Pro
- How do you find the middle of a linked list in one pass? Pro
- What edge cases must a robust doubly linked list implementation handle? Pro
- How do you detect and repair a corrupted or self-looping doubly linked list? Pro
Stack and queue problem patterns
Monotonic stacks and queues, sliding-window maximum, queues as the BFS frontier, and two-stack undo and redo.
- What problem shape does a monotonic stack solve at the concept level? Pro
- What problem shape does a monotonic queue solve at the concept level? Pro
- Why is a queue, not a stack, the right structure for a BFS frontier? Pro
- How would you design an undo and redo feature, and why two stacks? Pro
- How do you get the maximum over a sliding window using a deque? Pro
Call stack and recursion depth
What lives in a stack frame, why stack overflows happen, and how to replace recursion with an explicit stack for deep structures.
- Where does the call stack fit, and what lives in a stack frame? Pro
- What causes a stack overflow, and how deep can recursion go? Pro
- When should you replace recursion with an explicit stack? Pro
- How do you process a structure whose depth exceeds the stack limit? Pro
- How do you free a very long linked list without overflowing the call stack? Pro
Linked lists in real systems
Where linked lists earn their place: LRU caches, skip lists, intrusive lists, allocator free lists, and large-scale uses.
- How do skip lists use linked lists to get faster search? Pro
- Why is a doubly linked list the backbone of an LRU cache? Pro
- How do you build a fixed-capacity LRU cache from a map and a list? Pro
- How do intrusive linked lists reduce allocation overhead in systems code? Pro
- How do memory allocators use free lists built on linked lists? Pro
- When is a linked list still the right choice at large scale? Pro
Memory and cache performance
Cache locality, per-node memory overhead, cache misses and fragmentation in huge lists, and layouts like unrolled and XOR-linked lists.
- How does cache locality make arrays faster than linked lists in practice? Pro
- What is the real memory overhead of a linked list per element? Pro
- What cache-miss costs appear when a linked list grows to millions of nodes? Pro
- How does an unrolled linked list trade node count for cache performance? Pro
- What causes memory fragmentation in a long-lived linked list? Pro
- How does XOR linking halve pointer memory, and why is it rarely worth it? Pro
- How do you maintain a linked list of a billion nodes, and what breaks first? Pro
Concurrent stacks, queues and lists
Thread-safe and lock-free queues and stacks, blocking queues, work-stealing deques, and safe iteration of shared linked lists.
- How does a work-stealing deque speed up parallel schedulers? Pro
- How do you make a queue thread-safe for many producers and consumers? Pro
- How would you design a bounded blocking queue? Pro
- How does a lock-free queue work, and what makes it so hard? Pro
- How do you make a stack thread-safe without serializing every operation? Pro
- How do you safely iterate a linked list while other threads mutate it? Pro
- What concurrency hazards come with a shared linked list, and how do you mitigate them? Pro
Queues at system scale
Backpressure and full buffers, multilevel scheduling, durable, sharded and delayed queues, and what breaks at very high throughput.
- How do schedulers use multiple queues to balance fairness and priority? Pro
- What happens to a ring buffer when producers outrun consumers? Pro
- How does backpressure work when a queue fills faster than it drains? Pro
- How would you make a queue durable across process restarts? Pro
- How do you shard a queue to scale past one machine's throughput? Pro
- How would you design a delayed or scheduled-delivery queue? Pro
- What breaks first when one queue must handle a million messages a second? Pro
All questions
Showing of 78What is a linked list, and how does it differ from an array?
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Last attempt -
A linked list chains elements together through nodes. Each node holds a value and a pointer to the next node. The list only knows where its first node lives, so you reach any element by following pointers one hop at a time.
An array stores elements side by side in one contiguous block. That layout lets you jump straight to index 5 by arithmetic. A linked list cannot, so reaching position 5 costs O(n) hops. Arrays give O(1) random access, and linked lists give O(n).
The tradeoff flips for growth. An array has a fixed block, so growing may mean copying everything. A linked list just allocates a node and rewires a pointer. Choose based on whether you index often or reshape often.
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What is the difference between a singly and a doubly linked list?
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A singly linked list gives each node one pointer, aimed at the next node. You can only walk forward, from the head toward the tail. To reach the previous node, you must restart from the head.
A doubly linked list adds a second pointer, aimed at the previous node. Now you can walk in both directions. Deleting a node you already hold becomes easy, since you reach its neighbor on each side directly.
That second pointer costs memory and upkeep. A million nodes carry a million more references, and each insert updates two links instead of one. Pick doubly when you delete or scan backward often, and singly when forward-only is enough.
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What is a stack, and what does LIFO actually mean?
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A stack is a pile where you only touch the top. You add items on top with push and take them off the top with pop. The bottom stays untouched until everything above it leaves.
LIFO means last in, first out. The most recently added item is the first one you get back. Think of a stack of plates. You wash the last plate you set down, not the first.
This ordering matters when you must reverse or backtrack. Browser back buttons, undo history, and function calls all rely on it. The newest work gets resolved first, while older work waits underneath.
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What is a queue, and what does FIFO actually mean?
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A queue is a waiting line. You add items at the back and remove them from the front. Nobody jumps ahead, so the order you arrive is the order you leave.
FIFO means first in, first out. The item that waited longest gets served next. A ticket counter works this way. The person at the front, who came earliest, is called first.
This fairness makes queues natural for scheduling and buffering. Print jobs, task runners, and message pipelines process work in arrival order. When order and fairness matter more than recency, a queue fits. It keeps the oldest waiting item from starving behind newer arrivals.
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What are the core operations of a stack, and what do they cost?
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A stack offers four operations.
pushadds an item to the top.popremoves and returns the top item.peekreads the top without removing it.isEmptyreports whether anything is left.
Each of these costs O(1). You only ever touch one end, so nothing shifts or searches. push and pop just adjust the top position and one value. peek reads a single slot. Calling pop or peek on an empty stack is an underflow, so check isEmpty first.
That constant cost is the whole appeal. No matter how many items sit below, the top operations stay instant. This is why stacks handle deep call chains and long undo histories without slowing down.
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What are the core operations of a queue, and what do they cost?
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A queue offers four operations, and every one costs O(1) when the queue is built well.
enqueueadds an item at the back.dequeueremoves and returns the item at the front.frontreads that front item without removing it.isEmptychecks whether any items remain.
You touch only the two ends, never the middle. A good design keeps a pointer to both ends, so neither operation walks the line.
How well it is built depends on the storage. A careless array-backed queue can drift or need shifting. Keeping both ends O(1) takes a ring buffer or a linked list.
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What do insertion and deletion cost in a linked list versus an array?
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Inserting or deleting in a linked list costs O(1) once you hold the right node. You rewire a pointer or two and you are done. Nothing else moves, and the rest of the list stays where it sat.
An array behaves differently. To insert or delete in the middle, you must shift every later element over one slot. That shift costs O(n). Only changes at the very end avoid it.
The catch is reaching the node. The linked list is O(1) only after you get there, and finding it first still costs O(n) hops. Arrays trade cheap access for expensive reshaping, and linked lists do the reverse.
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When should you use a linked list instead of an array?
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Reach for a linked list when you reshape more than you index. If you constantly insert and remove at points you already hold, its O(1) splicing wins. Queues, playlists, and edit histories fit this shape.
It also helps when size is unpredictable. A linked list grows one node at a time, with no big block to reserve or copy. You never pay a resize that duplicates the whole collection.
Skip it when you need fast access by position. Arrays give O(1) indexing and pack tightly in memory, so the processor's cache serves them quickly. If you mostly read by index, an array almost always wins.
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What is a deque, and what can it do that a stack or queue cannot?
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A deque, short for double-ended queue, lets you add and remove at both ends. Push and pop work on the front and on the back. It is a queue and a stack fused into one structure.
That is exactly what a plain stack or queue cannot do. A stack only touches one end. A queue adds at one end and removes at the other. Neither gives you free access to both ends at once.
This both-end access shows up in real work. Sliding-window scans, work-stealing schedulers, and browser history all rely on it. When a single end is not enough, a deque is the natural next step.
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How do you implement a stack, and what data structure backs it?
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You can build a stack on an array or on a linked list. Both keep push and pop at O(1). The choice mostly changes memory behavior, not the contract callers see.
With an array, you track the top index. push writes at that index and bumps it. pop reads and steps back. The array grows when full, occasionally copying everything to a bigger block.
With a linked list, the head node is the top. push adds a new head, and pop unlinks it. No copying ever happens, but each node costs an extra pointer.
stack.push(4); // top is now 4
stack.pop(); // returns 4, top restored
Most languages hand you a ready stack through their dynamic array type. Reach for that first.
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How do you implement a queue, and what data structure backs it?
Answer it yourself first - out loud, or typed below.
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A queue needs two access points, one end to add and another to remove. You back it with either a linked list holding head and tail pointers, or a ring buffer over a fixed array.
With a linked list, you enqueue at the tail and dequeue at the head, both O(1). The tail pointer is what keeps enqueue cheap. Without it, you would walk the whole list.
A ring buffer uses two indices that chase each other and wrap around the array. That gives O(1) operations with far better cache behavior and no per-node allocation. The catch is fixed capacity, so you either grow the array or reject when full.
Pick the ring buffer when throughput matters, like network packet handling, and the linked list when the queue must grow without bound.
This answer doesn't lend itself to a diagram - it reads best . No credits were charged.
Why there's no diagram: “”
The interactive diagram is below the answer - jump to diagram ↓ · Below it, the related concept . Jump to it ↓
How do you find the Nth element of a linked list, and what does it cost?
What is a node, and what does each node store in a linked list?
Why does a linked list keep a head pointer, and when do you add a tail?
What is a circular linked list, and where is it used?
What everyday problems do stacks naturally solve?
What everyday problems do queues naturally solve?
Why are stacks and queues defined by their operations rather than their storage?
What is the difference between a stack and a queue?
Why is random access slow in a linked list compared to an array?
How does cache locality make arrays faster than linked lists in practice?
What does a doubly linked list's extra pointer buy you, and what does it cost?
How does a sentinel node remove edge cases from list insertion and deletion?
How do you detect a cycle in a linked list, and what does the idea cost?
What is the idea behind reversing a linked list in place, and its cost?
Why is deleting a node hard when you only have a pointer to it?
What is the real memory overhead of a linked list per element?
When would you back a stack with an array versus a linked list?
When would you back a queue with an array versus a linked list?
Why does a naive array-backed queue waste space, and how do you fix it?
What is a ring buffer, and how do its head and tail wrap around?
How do you implement a deque so both ends stay O(1)?
How do you build a queue from two stacks, and what does it cost?
Why is push on a dynamic-array stack O(1) amortized but not worst case?
What problem shape does a monotonic stack solve at the concept level?
What problem shape does a monotonic queue solve at the concept level?
Where does the call stack fit, and what lives in a stack frame?
What causes a stack overflow, and how deep can recursion go?
When should you replace recursion with an explicit stack?
Why is a queue, not a stack, the right structure for a BFS frontier?
How does a priority queue differ from a plain FIFO queue?
How do skip lists use linked lists to get faster search?
Why is a doubly linked list the backbone of an LRU cache?
How does insertion into a sorted linked list compare to a sorted array?
What makes splicing or splitting linked lists cheap?
Why can't you binary search a linked list efficiently?
How do you implement a stack using queues, and what does it cost?
How do you find the middle of a linked list in one pass?
How do you implement a stack that returns its minimum in O(1)?
How do you build a fixed-capacity LRU cache from a map and a list?
How do you process a structure whose depth exceeds the stack limit?
How would you design an undo and redo feature, and why two stacks?
How do you get the maximum over a sliding window using a deque?
How do schedulers use multiple queues to balance fairness and priority?
How does a work-stealing deque speed up parallel schedulers?
How do you make a queue thread-safe for many producers and consumers?
How would you design a bounded blocking queue?
How does a lock-free queue work, and what makes it so hard?
How do you make a stack thread-safe without serializing every operation?
What happens to a ring buffer when producers outrun consumers?
How does backpressure work when a queue fills faster than it drains?
How would you make a queue durable across process restarts?
How do you shard a queue to scale past one machine's throughput?
How would you design a delayed or scheduled-delivery queue?
What breaks first when one queue must handle a million messages a second?
How do you free a very long linked list without overflowing the call stack?
What edge cases must a robust doubly linked list implementation handle?
How do you detect and repair a corrupted or self-looping doubly linked list?
How do you safely iterate a linked list while other threads mutate it?
What concurrency hazards come with a shared linked list, and how do you mitigate them?
What cache-miss costs appear when a linked list grows to millions of nodes?
How does an unrolled linked list trade node count for cache performance?
How do intrusive linked lists reduce allocation overhead in systems code?
How do memory allocators use free lists built on linked lists?
What causes memory fragmentation in a long-lived linked list?
How does XOR linking halve pointer memory, and why is it rarely worth it?
When is a linked list still the right choice at large scale?
How do you maintain a linked list of a billion nodes, and what breaks first?
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Linked Lists, Stacks & Queues in pictures.
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Linked Lists, Stacks & Queues cheatsheet
- Linked lists vs arrays01
- Linked list techniques02
- Stacks03
- Queues04
- Deques & sliding windows05
- Classic design questions06
- Recursion & the call stack07
- Thread-safe structures08
- Queues in production09
- Linked lists at scale10
- The model11
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