Software process analysis and improvement relies heavily on empirical research. Empirical research requires measurement, experimentation, and modeling. Moreover, whatever evidence is gained via empirical research is strongly context dependent. Thus, it is hard to combine results and capitalize upon them in order to improve software development processes in evolving development environments. The process simulation model GENSIM 2.0 addresses these challenges. Compared to existing process simulation models in the literature, the novelty of GENSIM 2.0 is twofold: (1) The model structure is customizable to organization-specific processes. This is achieved by using a limited set of macro-patterns. (2) Model parameters can be easily calibrated to available empirical data and expert knowledge. This is achieved by making the internal model structures explicit and by providing guidance on how to calibrate model parameters. This paper outlines the structure of GENSIM 2.0, shows examples of how to calibrate the simulator to available empirical data, and demonstrates its usefulness through two application scenarios. In those scenarios, GENSIM 2.0 is used to rank feasible combinations of verification and validation (V&V) techniques with regards to their impact on project duration, product quality and resource consumption. Though results confirm the expectation that doing more V&V earlier is generally beneficial to all project performance dimensions, the exact rankings are sensitive to project context.