Common Coding Interview Patterns
Master the essential patterns—sliding window, two pointers, fast-slow pointers—that solve 80% of linked list and array problems.
Posts tagged with #dsa
Counting Sort & Radix Sort: Linear-Time Sorting
Understand non-comparison sorting algorithms that achieve O(n+k) time complexity by exploiting known bounds on input values.
Depth-Limited & Bidirectional Search
Explore search algorithm variants: depth-limited search for bounded recursion, and bidirectional search for O(b^d/2) complexity improvement.
Depth-Limited Search: Bounded Depth-First Search
Learn depth-limited search (DLS) for handling infinite state spaces with a depth bound, and how it relates to iterative deepening.
Dijkstra's Algorithm: Finding Shortest Paths in Weighted Graphs
Master Dijkstra's algorithm for single-source shortest path problems in weighted graphs with positive edges, including implementations and trade-offs.
Divide and Conquer: Breaking Problems into Subproblems
Master the divide and conquer paradigm with classic examples like merge sort, quicksort, and binary search.
DP on Trees and Graphs: Tree DP and Graph DP
Apply dynamic programming to tree and graph structures using DFS-based state propagation for optimal subtree and path calculations.
DP States and Transitions: Building Optimal Solutions
Learn how to identify optimal substructure, define DP state variables, and formulate recurrence relations correctly.
Dynamic Programming: From Memoization to Optimal Solutions
Master dynamic programming fundamentals including memoization, tabulation, and how to identify DP subproblems.
Edit Distance: Transforming One String to Another
Solve the minimum edit distance problem using dynamic programming with applications in spell checking, DNA alignment, and autocomplete.