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Austin Mordahl

Incoming Assistant Professor

Chicago, IL

austin.mordahl@utdallas.edu

he/him/his


About Me

Update: I recently defended my dissertation!

I completed my Ph.D. at The University of Texas at Dallas. My faculty supervisor was Dr. Shiyi Wei.

I am joining UIC as an assistant professor this fall! I am actively looking for students who are interested in doing cutting edge research in software engineering, so if you're a current/incoming student to UIC, or interested in moving to UIC in the future, please feel free to reach out!


Research Interests

My research focuses on transforming software quality assurance approaches to make them more accurate and accessible to a wider audience and variety of use cases. My work so has primarily focused on static analysis and fuzzing; I have developed novel methods to automatically test and debug configurable analyses, and has advanced the understanding of the full behavior of such tools. I have also worked on applying machine learning for the tasks of triaging and automatically configuring static analysis tools, lifting static analysis to work on software product lines, and on improving evaluations of fuzz testing.



Awards

NSF Graduate Research Fellowship Awardee
2020

Eugene McDermott Graduate Research Fellowship Awardee
2020

ICSE 2019 Student Research Competition Winner
2019

Publications

RTL-Spec: RTL Spectrum Analysis for Security Bug Localization
Appearing in HOST 2024

Samit Miftah, Shamik Kundu, Austin Mordahl, Shiyi Wei, and Kanad Basu


ECSTATIC: An Extensible Framework for Testing and Debugging Configurable Static Analysis
ICSE 2023

Austin Mordahl, Zenong Zhang, Dakota Soles, Shiyi Wei

Download Here


ECSTATIC: Automatic Configuration-Aware Testing and Debugging of Static Analysis Tools
ISSTA 2023 Tool Demonstration

Austin Mordahl, Dakota Soles, Miao Miao, Zenong Zhang, Shiyi Wei

Download Here


Automatic Testing and Benchmarking for Configurable Static Analysis Tools
ISSTA 2023 Doctoral Symposium

Austin Mordahl

Download Here


An Empirical Assessment of Machine Learning Approaches for Triaging Reports of Static Analysis Tools
EMSE Vol 28, Issue 2, Article 28

Sai Yerramreddy, Austin Mordahl, Ugur Koc, Shiyi Wei, Jeffrey S. Foster, Marine Carpuat, Adam A. Porter

Download Here


SATune: A Study-Driven Auto-Tuning Approach for Configurable Software Verification Tools
ASE 2021

Ugur Koc, Austin Mordahl, Shiyi Wei, Jeffrey S. Foster, and Adam Porter

Download Here


The Impact of Tool Configuration Spaces on the Evaluation of Configurable Taint Analysis for Android
ISSTA 2021

Austin Mordahl, Shiyi Wei

Download Here


An Empirical Study of Real-World Variability Bugs Detected by Variability-Oblivious Tools
ESEC/FSE 2019

Austin Mordahl, Jeho Oh, Ugur Koç, Shiyi Wei, Paul Gazzillo

Download Here


Toward Detection and Characterization of Variability Bugs in Configurable C Software: An Empirical Study
ICSE 2019 Winner of the Student Research Competition

Austin Mordahl

Download Here


Program Committee Service

PLDI Artifact Evaluation Committee
2024

ECOOP Extended Review Committee
2024

ECOOP Artifact Evaluation Committee
2024

ECOOP Artifact Evaluation Committee
2024

ECOOP Artifact Evaluation Committee
2023

ASE Artifact Evaluation Committee
2022

PLDI Artifact Evaluation Committee
2022

ECOOP Doctoral Symposium
2020

Volunteer Service

CCS
2020

ESEC/FSE
2019