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EXE: Automatically Generating Inputs of Death 2025-09-17 · 22:30 Michael Vaughn – Senior Software Engineer @ Antithesis Autonomous testing complements conventional testing by leveraging cheap compute to explore software state spaces and 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. concolic execution symbolic execution fuzzing sat solvers software testing	Michael Vaughn on EXE: Automatically Generating Inputs of Death

Autonomous testing complements conventional testing by leveraging cheap compute to explore software state spaces and 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.

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