Dr. Mohammad Rezaalipour

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About Me

My name is Mohammad Rezaalipour, also known as Moe. I am a Postdoctoral Researcher with the Chair of Software Engineering I, at the University of Passau, located in the picturesque City of Three Rivers. I am working under the supervision of Professor Christian Hammer.

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Contact

I am mostly active on LinkedIn and use ResearchGate, Google Scholar, and GitHub for maintaining and sharing my academic and professional activities. Feel free to reach out to me through any of these platforms or via email.

Email: mohammad [dot] rezaalipour [at] uni-passau [dot] de

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Research Interests

I am particularly interested in:

• Software Testing and Analysis
• Software Fault Localization
• Automated Program Repair
• AI4SE and SE4AI

My vision is to implement the methods and techniques I propose in my research as open-source software tools.

• I developed PyLLMut, a Python library that uses LLMs to generate mutants for Python programs.

• As part of my PhD research, I developed FauxPy, which, to the best of my knowledge, is the only multi-family fault localization tool for Python that is available as open-source software. FauxPy has been tested with 135 real-world bugs across 13 widely used Python projects, such as Keras and Pandas.

• I also developed aNNoTest as part of my PhD research, an annotation-based test generation tool specifically designed for neural network programs. aNNoTest has been tested with 19 real-world neural network programs; it has found one bug and one documentation inconsistency in Vision, PyTorch’s machine vision library.

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Selected Publications

• EMSE: Mohammad Rezaalipour, Carlo A. Furia. (2024). “An Empirical Study of Fault Localization in Python Programs.” https://doi.org/10.1007/s10664-024-10475-3.

• ICSME: Mohammad Rezaalipour, Carlo A. Furia. (2023). “aNNoTest: An Annotation-based Test Generation Tool for Neural Network Programs.” https://doi.org/10.1109/ICSME58846.2023.00075.

• JSS: Mohammad Rezaalipour, Carlo A. Furia. (2023). “An annotation-based approach for finding bugs in neural network programs.” https://doi.org/10.1016/j.jss.2023.111669.

• TC: Morteza Rezaalipour, Mohammad Rezaalipour, Masoud Dehyadegari, Mahdi Nazm Bojnordi. (2020). “AxMAP: Making Approximate Adders Aware of Input Patterns.” https://doi.org/10.1109/TC.2020.2968905.

• FSEN: Babak Bagheri, Mohammad Rezaalipour, Mojtaba Vahidi-Asl. (2019). “An Approach to Generate Effective Fault Localization Methods for Programs.” https://doi.org/10.1007/978-3-030-31517-7_17.

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Education

• PhD in Informatics – Università della Svizzera italiana, Lugano
  • Supervised by Professor Carlo Alberto Furia
  • Thesis: Test Case Generation and Fault Localization for Data Science Programs
• Master’s in Software Engineering – Shahid Beheshti University, Tehran
  • Supervised by Professor Hassan Haghighi
• Bachelor’s in Robotics Engineering – Shahrood University of Technology, Shahrood

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