Dass Menschen anhand ihres Schreibstils identifizierbar sind, ist nichts neues. Vor zwei Jahren gab's einen Vortrag auf dem 29C3 über Sprachabdrücke in Underground-Märkten im Darkweb (aka Silkroad u.ä.) Jetzt hat eine neue Studie festgestellt, dass dasselbe Prinzip für Coding gilt und sich da längst nicht nur auf wiederverwendete Funktionen bezieht.
Researchers […] have developed a “code stylometry,” which uses natural language processing and machine learning to determine the authors of source code based on coding style. Their findings, which were recently published in the paper “De-anonymizing Programmers via Code Stylometry,” could be applicable to a wide of range of situations where determining the true author of a piece of code is important. For example, it could be used to help identify the author of malicious source code and to help resolve plagiarism and copyright disputes.
The authors based their code stylometry on traditional style features, such as layout (e.g., whitespace) and lexical attributes (e.g., counts of various types of tokens). Their real innovation, though, was in developing what they call “abstract syntax trees” which are similar to parse tree for sentences, and are derived from language-specific syntax and keywords. These trees capture a syntactic feature set which, the authors wrote, “was created to capture properties of coding style that are completely independent from writing style.”
IT World: CSI Computer Science: Your coding style can give you away (via /.)