Dr. Mohammad Rezaalipour

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About Me

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

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How to Reach Me

• Google Scholar
• DBLP
• ResearchGate
• ORCID
• GitHub
• LinkedIn
• Bluesky
• Mastodon
• X (Twitter)

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

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Research Interests

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

Open-Source Software Tools

(More details on the projects page)

• PyLLMut:
  A Python library that leverages LLMs to generate mutants for Python programs.

• FauxPy:
  To the best of my knowledge, the only open-source, multi-family fault localization tool for Python.
  Developed during my PhD, FauxPy has been tested on 135 real-world bugs across 13 widely used Python projects,
  including Keras and Pandas.

• aNNoTest:
  An annotation-based test generation tool for neural network programs, developed as part of my PhD research.
  aNNoTest has been evaluated on 19 real-world neural network programs, uncovering:

  • One bug
  • One documentation inconsistency
    both in Vision, PyTorch’s computer vision library.

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Selected Publications

(See the full list on the publications page)

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

• ICSME (2023):
  aNNoTest: An Annotation-Based Test Generation Tool for Neural Network Programs
  Mohammad Rezaalipour, Carlo A. Furia
  DOI: 10.1109/ICSME58846.2023.00075

• JSS (2023):
  An Annotation-Based Approach for Finding Bugs in Neural Network Programs
  Mohammad Rezaalipour, Carlo A. Furia
  DOI: 10.1016/j.jss.2023.111669

• IEEE Transactions on Computers (2020):
  AxMAP: Making Approximate Adders Aware of Input Patterns
  Morteza Rezaalipour, Mohammad Rezaalipour, Masoud Dehyadegari, Mahdi Nazm Bojnordi
  DOI: 10.1109/TC.2020.2968905

• FSEN (2019):
  An Approach to Generate Effective Fault Localization Methods for Programs
  Babak Bagheri, Mohammad Rezaalipour, Mojtaba Vahidi-Asl
  DOI: 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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