Biography
Austin Mordahl is an Assistant Professor at the University of Illinois Chicago as of November 2024. His research interests are in software testing and program analysis. He has focused on transforming software quality assurance (SQA) processes (such as fuzzing and static analysis) to make them more accurate and accessible. His work has applied approaches like testing, static analysis, and machine learning towards this goal.
Talk: “Improving Confidence in Static Analysis Tools via Metamorphic Testing”
Abstract: As software gets larger and more complex, it becomes more and more important to thoroughly verify that it is free from critical errors. Static analysis tools are well-suited to this task, but as complex pieces of software themselves, they may have bugs that compromise the accuracy and reliability of the results. These tools are difficult to test because of the oracle problem, i.e., it is difficult to determine what the correct output of a static analysis for a non-trivial program should be. Metamorphic testing has emerged as a common approach to overcome the oracle problem. In metamorphic testing, related inputs are fed to the software under test, with the expectation that there should be some observable relation between the outputs. In this talk, we will explore approaches to metamorphic testing of static analysis tools, in order to find bugs and ultimately make these tools more reliable and correct.