Detection and Classification of Cross-language Code Clone Types by Filtering the Nodes of ANTLR-generated Parse Tree

Abstract

A complete and accurate cross-language clone detection tool can support software forking process that reuses the more reliable algorithms of legacy systems from one language code base to other. Cross-language clone detection also helps in building code recommendation system. This paper proposes a new technique to detect and classify cross-language clones of C and C++ programs by filtering the nodes of ANTLR-generated parse tree using a common grammar file, CPP14.g4. Parsing the input files using CPP14.g4 provides all the lexical and semantic information of input source code. Selective filtering of nodes performs serialization of two parse trees. Vector representation using term frequency inverse document frequency (TF-IDF) of the resultant tree is given as an input to cosine similarity to classify the clone types. Filtered parse tree of C and C++ increases the precision from 51% to 61%, and matching based on renaming the input/output expressions provides average precision of 91.97% and 95.37% for small scale and large scale repositories respectively. The proposed cross-language clone detection exhibits the highest precision of 95.37% in finding all types of clones (1, 2, 3 and 4) for 16,032 semantically similar clone pairs of C and CPP codes.

CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model

“…The AST uses ANTLR parser to evaluate the abstract view of each document in a hierarchical fashion for different types of codes, such as Java, C#, and C++. The ANTLR 34 is an effective parser producer which can read, examine, execute, and interpret hierarchical programming codes. It is often used to build parsers that can traverse syntax trees.…”