Numerical programs often use parallel programming techniques such as OpenMP to compute the
program's output values as efficient as possible. In addition derivative values of these
output values with respect to certain input values play a crucial role. To achieve code that
computes not only the output values simultaneously but also the derivative values this work
introduces several source-to-source transformation rules. These rules are based on a technique
called algorithmic differentiation. The main focus of this work lies on the important reverse
mode of algorithmic differentiation. The inherent data-flow reversal of the reverse mode must
be handled properly during the transformation. The first part of the work examines the
transformations in a very general way since pragma-based parallel regions occur in many
different kinds such as OpenMP OpenACC and Intel Phi. The second part describes the
transformation rules of the most important OpenMP constructs.
