Introduction

TRAKLA2 exercises are intended for Data Structures and Algorithms course. Each exercise is an independent learning object that you can interact with and receive immediate feedback on your performance in terms of automatic assessment, i.e., the system reports the number of correct steps out of the maximum steps when requested. In addition, the model solutions are available for each exercise. Watch the tutorial video or refer to the documentation in our research site to learn more about the exercises.

All you need to do the exercises is a Java enabled web browser. We have two versions available. The full TRAKLA2 learning environment requires registration and on-line connection while solving an exercises. However, we have also provided the following TRAKLA2 exercise package with reduced functionality (Grading does not submit the answer anywhere) that can be used off-line without an internet connection. For example, a lecturer can demonstrate the working of an algorithm or a learner is able to practise an algorithm after the lecture. Each time an exercise is initialized, a new instance of the exercise is produced, thus making it possible to provide individually tailored exercises and allow practise an algorithm with unlimited number of times.

Exercises

The material (currently over 50 exercises and their variations) is divided into the following 8 categories according to their topic. In addition, we have combined a set of exercises related to binary heaps to form an example tutorial covering also the theory and analysis of these algorithms. See the Algoviz project for more details. We hope to see more tutorials in the future to cover also other topics.

Basic algorithms Binary search Interpolation search Preorder Preorder with stack Inorder Postorder Levelorder Postfix evaluation Infix to Postfix Dynamic programming Sorting algorithms Quicksort Radix-exchange-sort Counting methods for sorting Mergesort (iterative) Mergesort (recursive) Heapsort Selection sort Insertion sort Priority queues Build heap Heap operations Build heap MinHeap Insert MinHeap Delete

Search trees Binary Search Tree Search Binary Search Tree Insertion Binary Search Tree Deletion 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 Hashing Linear probing Quadratic probing Double hashing Separate chaining Rehashing Graph algorithms BFS DFS Prim‘s algorithm Dijkstra‘s algorithm Dijkstra's algorithm with heap

Analysis Running time of recursive algorithms Running time of iterative algorithms Asymptotic analysis Order of Growth 1 Order of Growth 2 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 Polygon Traversal Line Sweep Visibility with Rotational Sweep Expanding Wave-method Adding a point to TIN Voronoi Construction Polygon Skeleton