System Dynamics (SD) is a special type of simulation modeling where 
output validity refers to validating the patterns of dynamic behaviors, such 
as oscillations, growth or decline. The developers and users of these 
models (the decision makers and people affected by decisions based on 
such models) are all rightly concerned with whether a model and its 
results are “valid.” Structural model validity and validation have long been 
recognized as one of the main issues in system dynamics. This concern 
is addressed through pattern recognition and testing in this paper. 
Another issue in dynamic simulation methodology is parameter 
calibration; assuming that the structure of simulation model constructed 
by the user is valid. Parameter calibration is the minimization of an error 
function which is a measure of the correspondence between numerically 
calculated output patterns and the respective real behavior patterns. We 
offer a software that does automated parameter calibration with respect to 
a given (desired) dynamic pattern. This particular feature can also be 
used in policy improvement design.