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\begin{abstract}
\acrshort is an automatic complexity analysis tool for integer
programs, which was recently extended to the analysis of probabilistic
integer programs. Currently, \acrshort applies so-called control-flow
refinement via partial evaluation to classic programs by calling the tool
iRankFinder externally. In this thesis, we extend partial evaluation to
probabilistic programs. A partially evaluated probabilistic integer program
has the same expected runtime complexity as the original program. However,
the transformed program might be easier to analyse. The new algorithm is
implemented natively in \acrshort and it is integrated into the
existing analysis algorithm modular and on demand. Our evaluation shows that
the native implementation is faster on classical programs. Furthermore, the
new implementation also infers tighter runtime complexity bounds for some
probabilistic programs.
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