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Mastery Quizzes

You read the tutorial. Now explain the why, spot the tradeoffs, and put the concepts to work.

Pick from 45 quizzes covering the technical tutorials and labs in our data structures and algorithms series. Each has 24 multiple-choice questions, from a gentle warm-up to scenarios that make you think. You get an explanation after every answer, including the ones you get right. There is no timer, no sign-up wall, and no penalty for coming back to try again.

Data Structures

Introduction to data structures

Choose how to organize data by comparing the work of adding, finding, and removing it.

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Big-O Notation

Predict how work and memory grow, then choose an approach that fits the job.

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Arrays

Trace array operations, explain their costs, and pick the right collection for a real workload.

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Linked Lists

Follow the pointers, catch hidden traversal costs, and choose the right kind of list.

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Stacks

Trace LIFO operations, inspect the JavaScript wrapper, and reason about undo, copying, and storage costs.

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Queues

Predict FIFO behavior, follow linked-list queue operations, and compare ordering and performance tradeoffs.

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Trees

Read parent-child relationships, calculate height and depth, and decide when a hierarchy fits your data.

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Binary trees

Distinguish full, complete, perfect, and balanced trees, and check whether linked nodes form a valid binary tree.

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Binary search trees

Trace insertion and deletion, check subtree ordering, and explain how tree height affects search.

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Heaps

Follow a priority through array-backed heaps, predict bubbling, and separate heap order from a fully sorted collection.

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Hash tables

Use keys and values, recognize collisions, and reason about Map behavior and hash-table lookup costs.

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Hash functions

Trace toy hashes, explain collisions and avalanche behavior, and choose hashing tools without confusing a digest with encryption.

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Tries and prefix trees

Build shared prefixes, distinguish words from partial matches, and delete entries without damaging their neighbors.

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Bloom filters

Interpret definite negatives and possible matches, follow bit updates, and weigh memory against unnecessary lookups.

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Graphs

Model directed and undirected relationships, read adjacency lists, and keep edges consistent as a graph changes.

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Grid basics

Turn locations into row-column addresses, map clicks to cells, and choose how much detail a grid needs.

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Grid movement and boundaries

Translate directions into coordinates and keep invalid candidate moves from changing the real position.

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Grid movement with obstacles

Separate an existing cell from a usable one, trace collision checks, and keep movement and obstacle data consistent.

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Grid pathfinding with BFS

Predict the search frontier, rebuild routes from breadcrumbs, and explain the limits of shortest-step navigation.

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Merkle trees

Trace hash changes, reconstruct inclusion proofs, and separate snapshot integrity from trust and freshness.

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Algorithms Basics

Recursion

Follow calls down to a base case and back again, then distinguish smaller subproblems from less total work.

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Fibonacci beyond recursion

Compare repeated recursion, shared memoization, and rolling iteration without confusing call count, depth, or precision.

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Linear search

Trace first-match and all-match searches, reason about equality, and include scan and result-storage costs.

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Binary search

Maintain a valid search interval, trace midpoint decisions, and account for sorting, duplicates, and access costs.

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Binary tree traversal

Track discovery and exploration, compare queue and stack order, and read the returned nodes correctly.

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DFS and BFS

Explore cyclic graphs, distinguish visitation from routes, and select a traversal that matches the task.

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DFS and BFS lab

Predict worklist changes and separate the lab's visited order, discovery parents, and returned route.

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Dijkstra's shortest path

Relax weighted routes, choose the cheapest frontier, and understand when a tentative distance becomes final.

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Dijkstra lab

Read tentative-distance snapshots, predict relaxations, and test weighted-route claims with controlled graph changes.

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Sorting Algorithms

Selection sort

Trace minimum selection, compare the two collection variants, and weigh comparisons against swaps.

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Insertion sort

Move active values into a sorted prefix and explain stability, shifts, and nearly sorted inputs.

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Quicksort

Partition around a pivot, trace the actual two-pointer code, and reason about balance, stack space, and ties.

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Bubble sort

Follow adjacent swaps, prove what a quiet pass means, and distinguish swap count from scan cost.

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Counting sort with negative values

Translate signed keys into count-table positions without losing numeric order or overlooking range costs.

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Merge sort

Merge sorted runs, preserve equal-key order, and account for the real costs of array access and storage.

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Bogosort

Inspect random shuffles, distinguish expected work from guarantees, and see why luck is not a sorting strategy.

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Sorting stability

Track equal-key records, combine sorting passes, and distinguish stable behavior from names and coincidences.

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Counting sort

Build frequency tables, place repeated values, and decide when the key range makes counting worthwhile.

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Radix sort

Trace stable digit passes, understand the signed-number wrapper, and separate bucket size from total cost.

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Timsort

Recognize natural runs, follow stable merging, and understand which hybrid-sort details depend on the implementation.

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Default sorting algorithms

Choose built-in sorts by their contracts, understand hybrid trade-offs, and avoid outdated runtime assumptions.

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Diving Deeper

Sieve of Eratosthenes

Find primes by crossing out composites, trace the code, and decide when a sieve is worth its memory.

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Towers of Hanoi

Plan legal disk moves, follow the recursive calls, and see why a short program can describe an enormous job.

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Monty Hall Problem

Use informed reveals to reason about switching, check a simulation, and spot when different rules change the odds.

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Sierpinski Triangle

Build a fractal from smaller triangles, trace its stopping rule, and balance visible detail against growing work.

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Make the next attempt count

Your score comes with a review of missed concepts and links back to the relevant parts of the tutorial. Read those explanations, try a fresh attempt, and see what sticks. Score above 80% for a confetti celebration.

Want to keep track? After a quiz, connect your existing kirupa forum account and choose to save the result. Your results page shows every saved attempt, your best score for each topic, and an overall score based on your latest attempts.

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