In many articles, the terms Generative Artificial Intelligence and Machine Learning are used, and it is not always easy to classify them correctly or understand their differences. This blog will help you gain clarity quickly.

What is Machine Learning?

Definition and Purpose

Machine Learning (ML) is a subfield of Artificial Intelligence. Its goal is to enable machines to identify patterns in data and make predictions – without explicit programming. These systems learn from examples and improve with experience.

Typische Anwendungen im Softwaretest

Defect prediction based on historical bugs

Anomaly detection in system logs

Regression risk analysis for test case prioritization
 

Most commonly applied: Supervised Learning with labeled data. Alternatively: Unsupervised Learning for pattern recognition without predefined categories.

What is Generative AI?

Definition and Purpose

Typische Anwendungen im Softwaretest

Comparison: Machine Learning vs. Generative AI

Tools for Generative AI in Software Testing

ChatGPT

GitHub Copilot

Conclusion and Outlook

Summary

Future Outlook