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Algorithm Visualizer

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Learning ToolsAlgorithm Complexity ReferenceAlgorithm Learning Paths
Data StructuresArrayLinked ListStackQueue and DequeBinary Search TreeBinary HeapHash TableGraphTrieDisjoint Set UnionLRU CacheSkip ListSegment TreeB+ TreeBloom FilterFenwick Tree
SortingBubble SortCocktail Shaker SortBitonic SortSelection SortInsertion SortBinary Insertion SortShell SortMerge SortTop-Down Merge SortQuick SortThree-Way Quick SortDual-Pivot Quick SortHeap SortCounting SortRadix SortBucket Sort
Graph AlgorithmsDijkstra's Shortest PathKruskal's Minimum Spanning TreePrim's Minimum Spanning TreeBellman-Ford Shortest PathsTopological SortFloyd-WarshallStrongly Connected Components2-SATMaximum FlowBipartite MatchingLowest Common AncestorEulerian Path
Dynamic ProgrammingEdit Distance0/1 KnapsackUnbounded KnapsackLongest Common SubsequenceLongest Increasing SubsequenceCoin ChangeStone MergingTraveling Salesperson DPTree Dynamic ProgrammingDigit DPRerooting DP
Backtracking and SearchN-QueensSubsetsPermutationsCombination SumMaze Solving with DFSNumber of IslandsWord SearchSudoku SolverA* Search
StringsKMP String MatchingRabin-Karp String MatchingBoyer-Moore String MatchingManacher's Longest Palindromic SubstringSuffix ArrayLCP ArrayAho-Corasick AutomatonZ Function
Math and Number TheorySieve of EratosthenesLinear SieveEuclidean AlgorithmBinary ExponentiationExtended Euclidean AlgorithmChinese Remainder TheoremEuler's Totient FunctionMiller-Rabin Primality TestFast Fourier TransformPollard's Rho Factorization
Computational GeometryConvex HullRotating CalipersClosest Pair of PointsLine Segment IntersectionBentley-Ottmann Sweep Line
SearchingBinary SearchLower and Upper BoundSearch in a Rotated Sorted ArrayBinary Search on the AnswerTernary Search

Segment Tree

Hierarchical aggregates for dynamic range queries

Store an answer for every power-of-two segment

Each leaf represents one array element, and every internal node combines the answers of its two children. A query interval is decomposed into a small set of disjoint nodes whose segments fit completely inside it.

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Choose a range and sum a few precomputed segments instead of scanning every value.

A point update changes one leaf and recomputes ancestors to the root. Both range query and point update touch O(log n) tree levels; the complete structure uses O(n) memory.

General form: replace sum with any associative combine operation, such as minimum, maximum, greatest common divisor, or a custom record. Lazy propagation extends the structure to range updates.

For prefix sums with smaller constants, compare the Fenwick Tree.