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Mastering Hash Maps in Interview Settings
Learn how to recognise hash map opportunities, pick collision strategies, and explain amortised behaviour with confidence.
Hash MapData Structure
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16 articles
Hands-on guides that teach core data structures and patterns from first principles.
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Building a Trie from Scratch
Construct a prefix tree that supports insert and search in O(L), and learn how to extend it for autocomplete prompts.
TriePrefix Tree
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Interview Flowchart — A 20-Minute Diagnostic
Turn the Interview Flowchart into a repeatable script: clarify, pattern match, and choose the right tool without freezing mid-round.
Interview StrategyProblem SolvingFlowchart
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Backtracking Fundamentals — Exploring All Possibilities
Master the backtracking pattern by learning when to explore paths, how to prune invalid branches, and why state management is critical.
BacktrackingRecursionDFS
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Breadth-First Search — Level Order Thinking
Learn how BFS explores graphs layer by layer, powers shortest unweighted paths, and pairs perfectly with queues.
BFSGraphsTraversal
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Depth-First Search — Recursive and Iterative Patterns
Understand DFS as a flexible template for exploring as far as possible, powering cycle detection, connected components, and backtracking.
DFSGraphsRecursion
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Binary Search — Shrinking Search Space with Confidence
Internalise the binary search loop so you can apply it to sorted arrays, answer-range problems, and monotonic predicates.
Binary SearchArraysAlgorithm
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Dijkstra’s Algorithm — Weighted Shortest Paths
Move beyond unweighted graphs by mastering Dijkstra’s priority-queue based approach to shortest paths with non-negative weights.
DijkstraGraphsShortest Path
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Graph Representation Toolkit — Modeling Real Problems
Translate interviews into graph problems by choosing the right representation: adjacency lists, matrices, edge lists, and implicit neighbors.
GraphsData Modeling
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Heaps & Priority Queues — Controlling Extremes Fast
Learn how heaps provide O(log n) insertions and removals for extreme values, powering top-K, scheduling, and streaming problems.
HeapPriority QueueData Structure
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Kadane’s Pattern — Linear-Time Maximum Subarray
Use Kadane’s dynamic programming insight to find maximum subarray sums, track boundaries, and pivot to 2D variations.
Dynamic ProgrammingKadaneArrays
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Linked List Fundamentals — Pointers with Purpose
Demystify singly and doubly linked lists, pointer manipulation, and fast/slow patterns that dominate interview questions.
Linked ListPointers
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Pattern Searching in Strings — Sliding Windows & Prefixes
Master core string search techniques: naive sliding window, Rabin-Karp hashing, and prefix-function-based KMP.
StringsPattern Searching
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Queue Patterns — First-In, First-Out Workflows
Learn how queues model real-world workflows, feed BFS, and support monotonic optimisations like sliding window maximum.
QueueData Structure
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Sorting Strategies — Choosing the Right Order
Compare sorting algorithms, understand when to reach for mergesort vs. quicksort, and explain stability, in-place trade-offs, and custom comparators.
SortingAlgorithm
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Topological Sort — Ordering with Dependencies
Learn how to order tasks with prerequisites using Kahn’s algorithm or DFS post-order, and recognise when topological sort applies.
Topological SortGraphsDAG
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