“PerfFuzz: Automatically Generating Pathological Inputs,” written by graduate students Caroline Lemieux and Rohan Padhye, and Profs. Koushik Sen and Dawn Song, will receive a Distinguished Paper Award from the ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA) 2018 in Amsterdam in July. PerfFuzz is a method to automatically generate inputs for software programs via feedback-directed mutational fuzzing. These inputs exercise pathological behavior across program locations, without any domain knowledge. The authors found that PerfFuzz outperforms prior work by generating inputs that exercise the most-hit program branch 5x to 69x times more, and result in 1.9x to 24.7x longer total execution paths.