Cause-and-effect relationships in analysis of unobservable process properties

When implementing information technology, there exist sequences of objects that can be identified but it is difficult or impossible to observe their properties. In some objects of such sequences, an unobservable property $A$ may appear, the detection of which is of interest. To identify objects with property $A$, one has to use the search for the effects of property $A$ as the cause of such effects. If one considers a sequence of objects in which objects with property $A$ may appear, then there are problems of assessing the probability of the existence of false objects with the identified property $A$ when it actually does not exist (false alarms) and estimating the probability of skipping the object with property $A$. The work uses the determinism of the occurrence of effects when the cause appears, if there is an interaction of the object containing the cause with the object containing the observed effect. In this case, the existence of noise is allowed which makes it difficult to observe the effect when it is, and can create a false effect when the cause is absent. The methodology for assessing the probability of identifying objects with property $A$ constructed in the work is quite easy to use but is important in assessing the solvability of a search problem.