Using MaltParser for Fact Extraction from Programs

We present a novel approach to extract structural information from source code using state-of-the-art parser technologies for natural languages. The parser technology is robust in the sense that it guarantees to produce some output, entailing that even incomplete or incorrect source code as input will get some kind of analysis. This comes at the expense of possibly assigning a partially incorrect analysis for input free of errors. However, an evaluation on source codes of the Java, Python and C/C++ languages shows that the committed errors are few ie, our accuracy is close to 100%. The error analysis indicates that the majority of the errors remaining are harmless.