Abstract
The different ways of representing a source code in different programming languages create a heterogeneous context. In addition, the use of multiple programming languages in a single source code (polyglot programming) brings a wide choice of terms from different languages, libraries and structures. These facts prevent the direct exchange of information between source codes of different programming languages, requiring specialized knowledge of the programming languages involved. In this article, we present an ontology-based method for source code interoperability that provides an alternative to mitigate heterogeneity problems, aiming to semantically represent the source code written in different programming languages and apply it from different perspectives in a unified way. In this sense, the method is applied in a lab experiment with the objective of validating its methodological aspects, instantiating their respective phases in different subdomains (object orientation and object/relational mapping) and programming languages (Java and Python) in the code smells detection perspective. In addition, the code smell detector produced is evaluated with a set of real-world software projects written in Java and Python.
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