Anschaulich gestaltete Übungen helfen sowohl beim Bearbeiten der Übungsblätter als auch beim Lernen auf die Klausur.
Natürlich können auch andere Interessenten der Informatik und nicht nur Studenten mit der App einen Einblick in einige Algorithmen und Datenstrukturen erhalten.
Die App gliedert sich in folgende Themen:
- Laufzeit
- Suchen
- Sortieren
- Hashing
- Graphen
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Es gibt Übungen zu folgenden Unterthemen:
Laufzeit:
- Definitionen (Multiple Choice)
- Rechnen in O-Notation
- Code-Analyse
- Logarithmus
Suchen:
- Definitionen (Multiple Choice)
- Einfügen in AVL-Bäume
- Löschen aus AVL-Bäumen
- Einfügen in B-Bäume
- Löschen aus AVL-Bäume
- AVL-Bäume: Balance bestimmen (+,-,=)
Sortieren:
- Definitionen (Multiple Choice)
- Bubble Sort
- Insertion Sort
- Quick Sort
- Merge Sort
- Heap Sort
Hashing:
- Definitionen (Multiple Choice)
- Offenes Hashing
- Lineares Hashing
- Modulararithmetik
Graphen:
- Definitionen (Multiple Choice)
- Bestimmen der Adjazenzmatrix
- Minimaler Spannbaum
- Breitendurchlauf
- Tiefendurchlauf
- Kurze Wege (Single-Source-Shortest-Path-Problem)
Die meisten Aufgaben (außer Multiple Choice) werden per Random erzeugt, sodass es keinen Auswendig-Lern-Effekt gibt. Sie können diese Aufgaben immer wieder machen, um ein Thema zu verstehen.
Anleitungen helfen dabei, mit den Aufgaben vertraut zu werden.
Und Punkte, die man für alle Aufgaben und Kategorien nach erfolgreichem Abschließen der Aufgabe erreicht, geben Auskunft darüber, welche Themen man bereits gut verstanden hat. Algorithms and data structures is a learning app that is designed especially for computer science students who attend the corresponding lecture "Algorithms and Data Structures".
Clearly designed exercises help both when editing the exercise sheets and learning on the exam.
Of course, other interested parties and the computer science students not only with the app can get a glimpse of some algorithms and data structures.
The app is divided into the following topics:
- Duration
- Look for
- Order
- Hashing
- Graphs
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There are exercises for the following sub-themes:
Running time:
- Definitions (Multiple Choice)
- Convert in O notation
- Code analysis
- Logarithm
Look for:
- Definitions (Multiple Choice)
- Paste in AVL-Trees
- Delete from AVL trees
- Insert in B-trees
- Delete from AVL trees
- AVL Trees: Balance determine (+, -, =)
Order:
- Definitions (Multiple Choice)
- Bubble Sort
- Insertion Sort
- Quick Sort
- Merge Sort
- Heap Sort
Hashing:
- Definitions (Multiple Choice)
- Open Hashing
- Linear Hashing
- Modular arithmetic
Graph:
- Definitions (Multiple Choice)
- Determining the adjacency matrix
- Minimum spanning tree
- Breadth-first traversal
- Depth first
- Short paths (single-source shortest path problem)
The most tasks (except Multiple Choice) are generated by random, so there is no rote-learning effect. You can make these tasks again and again to understand a topic.
Instructions help to be familiar with the tasks.
And points that can be reached for all tasks and categories after successfully completing the task, provide information about which topics you have already well understood.
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