What algorithm visualizers are available on Code Visualizer?

Code Visualizer provides 10 interactive algorithm visualization modules: Sorting (Bubble, Selection, Insertion, Merge, Quick), Searching (Linear, Binary), Sliding Window, Two Pointers, Pathfinding (BFS, DFS, Dijkstra, A*), Recursion Trees, Dynamic Programming (Knapsack, LCS), String Matching (KMP, Rabin-Karp), Backtracking (N-Queens, Sudoku), and Greedy algorithms.

How does the sliding window algorithm visualizer work?

The sliding window visualizer animates both fixed-size and variable-size window techniques on arrays and strings. You can watch left and right boundary pointers expand and contract in real-time while the window state, running sum, and maximum values update step-by-step.

Why should I use an algorithm visualizer for coding interview preparation?

Algorithm visualizers build spatial intuition for how pointers move, recursion unwinds, and dynamic programming tables populate. Seeing algorithms execute on dynamic inputs helps software engineers retain patterns and solve LeetCode problems faster during technical interviews.

What is the difference between Dijkstra and A* pathfinding?

Dijkstra's algorithm explores all directions equally by prioritizing nodes with the lowest cumulative cost, guaranteeing the shortest path but visiting more nodes. A* enhances Dijkstra by adding an admissible heuristic (estimated distance to target), directing search toward the goal and visiting significantly fewer nodes while maintaining optimality.

Algorithm Visualizations

Watch algorithms in action with real-time animations. Adjust speed, change inputs, and compare different approaches.

Visualize this algorithm Try this example Run in playground

Algorithm:

Size:30

50%

Comparisons:0

Swaps:0

Bubble Sort

Best Case

O(n)

Average

O(n²)

Worst Case

O(n²)

Space

O(1)

Stable

Yes

Default

Comparing

Swapping

Sorted

Pivot

Minimum

About the Algorithm Visualizer

Code Visualizer's algorithm visualizer brings sorting, searching, pathfinding, dynamic programming, sliding window, two pointers, and greedy algorithms to life with real-time animations. Watch Bubble Sort swap elements, see Dijkstra's shortest path unfold on a grid, animate the sliding window technique on arrays, or trace recursive call trees for Fibonacci — all step by step.

Sliding Window Technique

Master the sliding window pattern used in coding interviews. Visualize fixed-size windows for maximum sum subarray (Kadane's variant) and variable-size windows for longest substring without repeating characters. See how the window expands and shrinks in real-time.

Two Pointer Technique

Understand the two-pointer approach for sorted arrays and optimization problems. Watch pointers converge in Two Sum, see container boundaries shift in Container With Most Water, and track the slow/fast pointer pattern for removing duplicates.

Greedy Algorithms

See how greedy algorithms make locally optimal choices. Visualize Activity Selection on a timeline, watch Fractional Knapsack fill by value-to-weight ratio, and observe Job Sequencing assign tasks to deadline slots for maximum profit.

Understanding Big O notation becomes intuitive when you can see the difference between O(n²) and O(n log n) play out visually. This visual learning tool doubles as a code debugger for algorithm logic, making it ideal for coding interviews, competitive programming prep, and computer science education. All 10 algorithm categories — Sorting, Searching, Sliding Window, Two Pointers, Pathfinding, Recursion, Dynamic Programming, Greedy, String Matching, and Backtracking — are interactive and animated.