
I am a researcher in the Software Lab focusing on automating software analysis and development.
Recently, I have been working on improving source code documentation by by introducing a novel attribute and a tool called Documentary to generate docstrings, an automated approach to generating proof-of-concept exploits for npm package vulnerabilities called PoCGen, a dynamic linter for Python called DyLin, mitigating hallucinations in LLM using iterative grounding, automatically generating tests, a novel metric to evaluate similarity in source code called CrystalBLEU, and the first general-purpose dynamic analysis framework for Python called DynaPyt.
My background includes work on distributed algorithms and distributed systems.
Aryaz Eghbali, Zhongxin Liu, Michael Pradel
FSE 2026
Aryaz Eghbali, Michael Pradel
ASE 2020
Aryaz Eghbali, Roger Wattenhofer
CBT 2019
Aryaz Eghbali, Philipp Woelfel
DISC 2018
2026 - present
Supervisor: Michael Pradel
Working on AI- and program analysis-based developer tools.
2020 - present
Supervisor: Michael Pradel
Working on AI- and program analysis-based developer tools.
Summer 2022
Supervisor: Max Schaefer and Frank Tip
Worked on automated test generation
2018 - 2019
Supervisor: Roger Wattenhofer
Worked on modeling the hardware usage by Bitcoin miners.
Summer 2018
Worked on analyzing in-app chat data to detect spam and offensive messages.
2014 - 2018
Supervisor: Philipp Weolfel
Thesis on proving a lower bound for abortable leader election algorithm.
2010 - 2014
ASE tutorial
2023
Dagstuhl Seminar on Programming Language Processing
2023