The automatic parallelization of loops that contain complex computations is still a challenge for current parallelizing compilers. The main limitations are related to the analysis of expressions that contain subscripted subscripts, and the analysis of conditional statements that introduce complex control flows at run-time. We use the term complex loop to designate loops with such characteristics. In this paper, we focus on the generation of parallel code for sequential complex loop nests using a generic compiler framework (proposed in an earlier paper [3]) that accomplishes kernel recognition through the analysis of the Gated Single Assignment program representation. Specifically, we present an extension of this framework that enables its use as a powerful tool for gathering source code information that is relevant for the parallelization of each computational kernel. A set of example codes are analyzed in detail to illustrate the potential of our approach. Experimental results using a benchmark suite of complex loop nests are also presented.