Machine learning techniques have been applied to the task of student modeling, more so in building tutors for acquiring programming skill. These were developed for various languages (Pascal, Prolog, Lisp, C++) and programming paradigms (procedural and declarative) but never for object-oriented programming in Java. JavaBugs builds a bug library automatically using discrepancies between a student and correct program. While other works analyze code snippets or UML diagrams to infer student knowledge of object-oriented design and programming, JavaBugs examines a complete Java program and identifies the most similar correct program to the student's solution among a collection of correct solutions and builds trees of misconceptions using similarity measures and background knowledge. Experiments show that JavaBugs can detect the most similar correct program 97% of the time, and discover and detect 61.4% of student misconceptions identified by the expert.