Algorithms – Fundamentals

This post is a glossary entry covering algorithm fundamentals – including key exam points, examples, and practice questions.

In a Nutshell

An algorithm is a clear, finite set of instructions that moves step-by-step from an initial state to a desired outcome.

Essential Properties

1. Clarity / Determinism
2. Executability / Effectiveness
3. Finiteness (Termination)
4. Determinism (in the exam context)
5. Generality (applies to a problem class)

Core Algorithm Building Blocks (High Exam Priority)

Every algorithm reduces to three fundamental structures – the basis for flowcharts (Nassi-Shneiderman diagrams):

Sequence

a = 5
b = 10
summe = a + b

Selection

WENN alter >= 18 DANN
  darfWählen = true
SONST
  darfWählen = false

Iteration

SOLANGE counter < 10
  print("Hallo")
  counter = counter + 1

Representation Methods

• Flowchart
• Flowchart diagram (high exam relevance)
• Pseudocode
• Program code

Algorithms You Need to Know

• Sorting: BubbleSort, QuickSort
• Searching: linear search, binary search (only on sorted data)

Common Exam Questions (Quick Answers)

1. What are the three fundamental building blocks of every algorithm? Sequence, selection, and iteration.
2. Why must an algorithm be finite? It must terminate – infinite loops are not a valid solution.
3. When can you use binary search? Only on sorted data.

Exam Tip

Practice flowcharts for:

• Finding the largest number in a list
• Checking odd/even
• Sum from 1 to n
• BubbleSort on a small list

More on Algorithms

Algorithms form the foundation of computer science and software development. The following articles will help you grasp all aspects of algorithms and apply them in practice.

Fundamentals and Properties

• Algorithms Fundamentals: Formulation and Application - Learn how to formulate algorithms and write pseudocode
• Algorithms Fundamentals: Complexity Analysis - Understand Big-O notation and complexity analysis
• Algorithms and Data Structures 2026 - Current overview of essential algorithms and data structures

Special Topics

• Algorithms Complexity and Security - Security aspects of algorithms
• Algorithms Searching, Sorting, and Recursion - Overview of important search and sort techniques