Automated Software Testing

fortiss advances the state-of-the-art in the field of software testing, focusing both on improving the efficiency of the testing process and enhancing the accuracy and completeness of the testing results. To this end, the researchers collaborate with industry partners to apply their research results in real-world settings.

The aim is to enhance the quality and reliability of software systems by 

• automating the testing process,
• reducing the need for manual testing and
• improving the overall efficiency of software development. 

In doing so, the researchers target the quality of software systems to reduce the likelihood of software failures in data-intensive applications, including web applications and artificial-intelligence-enabled cyber-physical systems such as autonomous vehicles.

Current main research areas include

• the robustness and maintainability of test suites (compilation of multiple test cases) for modern web applications,
• monitoring techniques and automated functional oracle (mechanisms for determining whether a test has passed or failed) for deep learning-based autonomous vehicles, and
• the transferability of test results from simulated to real platforms for cyber-physical systems.