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We present Stereocode, a static analysis tool engineered to automatically identify, and re-document software systems written in C++, C#, and/or Java with method and class stereotypes. A stereotype is a simple abstraction that encapsulates the high-level behavior of a method or a class. The tool is built around the srcML infrastructure, an XML representation of source code. Stereocode annotates the srcML input with the computed stereotypes as XML attributes to the function and class tags. We showcase Stereocode’s efficiency in conducting large-scale analysis of software systems, which involves using 1050 repositories from GitHub across C++, C#, and Java. The results provide valuable insights into the distribution of stereotypes. 

The work aims to enable the use of common software engineering techniques and tools for quantum programming languages (e.g., OpenQASM). With the increased interest in quantum computing, researchers are adopting the use of higher-level quantum programming languages versus low-level circuit diagrams. While general purpose programming languages (e.g., C++, Python) are highly supported by a variety of software engineering tools, these novel programming languages for quantum computing have almost no support. Useable tools for debugging, static analysis, error detection, and transformation are currently non-existent. This work extends an existing software infrastructure (i.e., srcML) for the analysis, exploration, and manipulation of source code to OpenQASM. The srcML infrastructure, via parsing, generates abstract syntax information of programs to support high-level querying and analysis of the source code. With this, quantum developers can extract information and identify possible errors or inefficiencies in their programs. The paper presents the basic syntactic markup for OpenQASM. Also, a number of relevant quantum-based problems (e.g., iteration patterns, control recusion) are described and examples of how they are addressed using srcML is given.