Programmers tend to have their own distinct styles, but it's not really feasible to pore over many lines of code looking for telltale cues about a program's author. Now, that might not be necessary. Researchers have developed a machine learning system that can 'de-anonymize' programmers, whether it's through raw source code or compiled binaries. As explained to Wired, the approach trains an algorithm to recognize a programmer's coding structure based on examples of their work, and uses those to pinpoint common traits in code samples. You don't need large chunks of a given program, either -- short snippets are often enough.