Clad is an automatic differentiation (AD) clang plugin for C++. Given a C++ source code of a mathematical function, it can automatically generate C++ code for computing derivatives of the function. Clad has found uses in statistical analysis and uncertainty assessment applications.
Object oriented paradigms (OOP) provide a structured approach for complex use cases, allowing for modular components that can be reused & extended. OOP also allows for abstraction which makes code easier to reason about & maintain. Gaining full OOP support is an open research area for automatic differentiation codes.
This project focuses on improving support for differentiating object-oriented constructs in Clad. This will allow users to seamlessly compute derivatives to the algorithms in their projects which use an object-oriented model. C++ object-oriented constructs include but are not limited to: classes, inheritance, polymorphism, and related features such as operator overloading.