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We're please to present Michael Vaughn on EXE: Automatically Generating Inputs of Death (read the paper)
Autonomous testing complements conventional testing by leveraging cheap compute to explore software state spaces & uncover unknown unknowns beyond human-written tests. It spans a spectrum from random-input fuzzing, which is fast but struggles with complex conditions, to symbolic execution, which uses SAT solvers to systematically reach hard-to-hit paths-though these solvers can become prohibitively slow on complex constraints. Exe strikes a balance through concolic execution: it runs bare-metal code on concrete inputs while instrumenting paths with logical constraints, invoking a solver only when needed to explore alternate branches. This approach combines the speed of concrete execution with the path-finding power of symbolic methods, avoiding the full cost of traditional symbolic engines.
Michael Vaughn (he/him) has a PhD in computer science from the University of Wisconsin-Madison, & is a senior software engineer at Antithesis, working on their hypervisor & fuzzer. He spent the better part of a decade doing research at the intersection of operating systems & programming languages, somehow managing to write concerning amounts of x86 assembly, C, Scheme, Haskell, & LaTeX, often in the same day. He has also worked as a pub trivia host, & loves board games, hiking, & reading.
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