  Static alias analysis of different type of programming languages has been
drawing researcher attention. However most of the results of existing
techniques for alias analysis are not precise enough compared to needs of
modern compilers. Probabilistic versions of these results, in which result
elements are associated with occurrence probabilities, are required in
optimizations techniques of modern compilers.
  This paper presents a new probabilistic approach for alias analysis of
parallel programs. The treated parallelism model is that of SPMD where in SPMD,
a program is executed using a fixed number of program threads running on
distributed machines on different data. The analyzed programs are assumed to be
in the static single assignment (SSA) form which is a program representation
form facilitating program analysis. The proposed technique has the form of
simply-strictured system of inference rules. This enables using the system in
applications like Proof-Carrying Code (PPC) which is a general technique for
proving the safety characteristics of modern programs.
