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@ast-fortiss-tum

Automated Software Testing

This is the GitHub group of the Automated Software Testing group at fortiss/TUM

Welcome to the Automated Software Testing (AST) group at fortiss/TUM! 👋

🧙 The organization contains the GitHub repositories with the research carried out at the Automated Software Testing (AST) Field of Competence at fortiss and the Chair of Software Engineering for Data-intensive Applications of the School of Computation, Information and Technology of the Technical University of Munich (TUM). You will find the algorithms and tools we developed in our research papers.

👩‍💻 Current projects involve test generation, monitoring techniques, automated functional oracles, and domain transferability for deep learning-based systems, with a particular focus on autonomous vehicles, as well as the robustness and maintainability of test suites of modern web applications.

👨‍👨‍👧‍👧 Our research focuses on the interface between software engineering and deep learning with the goal of improving the robustness, reliability, and dependability of data-intensive software systems.

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  1. opensbt-core opensbt-core Public

    ⚡ This project has moved to https://github.com/opensbt/opensbt-core (14-11-2024) ⚡

    Python 3 1

  2. misbehaviour-prediction-with-uncertainty-quantification misbehaviour-prediction-with-uncertainty-quantification Public

    Codebase of the MSc thesis by Ruben Grewal "Uncertainty Quantification for Failure Prediction in Autonomous Driving Systems" and replication package of the paper "Predicting Safety Misbehaviours in…

    Jupyter Notebook 2 1

  3. web-element-localization-using-similo-like-approaches web-element-localization-using-similo-like-approaches Public

    Codebase of the BSc thesis by Anton Kluge "Web Element Relocalization in Evolving Web Applications: Enhancing the VON Similo Approach"

    HTML

  4. I2I-quality-metrics-study I2I-quality-metrics-study Public

    Replication package of the paper "Assessing Quality Metrics for Neural Reality Gap Input Mitigation in Autonomous Driving Testing" (ICST 2024).

    Jupyter Notebook

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