Visit http://www.cs.hut.fi/Research/TRAKLA2/ or watch the video tutorial of the system.

Malmi, L., Karavirta, V., Korhonen, A., Nikander, J., Seppala, O., and Silvasti, P. Visual Algorithm Simulation Exercise System with Automatic Assessment: TRAKLA2. Informatics in Education Volume 3 3, 2 (2004), 267-288. http://www.vtex.lt/informatics_in_education/htm/INFE048.htm.

See also other publications.

From the project site webpage:

"TRAKLA2 is an automatic exercise system for learning data structures and algorithms. The system provides an environment to solve algorithm simulation exercises that can be automatically graded. The grading is based on comparison between the learner made simulation sequence and a sequence produced by an actual algorithm."

The back end to TRAKLA2 appears to be MatrixPro.

• Developer: Helsinki University of Technology (Finland); Ville Karavirta, Ari Korhonen, Lauri Malmi, and Kimmo Stålnacke
• Last updated: 2006-01-25
• Last visited: 2006-09-04

Trakkla is widely used in Finland (and might arguably be the AV project with the greatest number of total users). It is actively maintained as of 2009.

Algorithms and Data Structures Implemented

See TRAKLA2 exercises or create an account (takes a minute) at TRAKLA2.

1. Basic algorithms

• Evaluation of a postfix expression (A Tutorial)
• Infix to Postfix
• Binary search
• Interpolation search
• Preorder(with stack)
• Inorder
• Postorder
• Levelorder

2. Sorting algorithms

• Quicksort
• Radix-exchange-sort
• Counting methods for sorting
• Insertion sort
• Mergesort (recursive)
• Heapsort

3. Priority queues

• Build heap
• Heap operations
• Build heap

• MinHeap Insert

• MinHeap Delete

4. Search trees

• Binary Search Tree Search
• Binary Search Tree Insertion (variation)
• Binary Search Tree Deletion (variation)
• Faulty binary search tree
• Digital Search Tree
• Radix Search Tree
• Single rotation
• Double rotation
• AVL-tree insertion
• Red Black Tree
• Red Black Tree Coloring
• B-Tree
• Trie

5. Hashing

• Linear probing
• Quadratic Probing
• Double Hashing

6. Graph algorithms

• BFS
• DFS
• Prim‘s algorithm
• Dijkstra‘s algorithm (with heap)

7. Analysis

• Running time of recursive algorithms
• Running time of iterative algorithms
• Asymptotic analysis
• Order of Growth 1
• Order of Growth 2

8. Spatial Data Algorithms

• Point in Polygon
• Point in Polygon with R-Tree
• Douglas-Peucker Line Simplification
• Closest pair of points
• Point-Region Quadtree Insert
• R-Tree Insert
• Line Intersections Using Line Sweep
• Visibility with Rotational Sweep
• Expanding Wave-method
• Adding a point to TIN
• Voronoi Construction