DMN16 — ambiguity for collections

I do not understand the following aspect about collections: Assume the input data node is a collection, but the decision is NOT a collection. From my understanding, the individual values of the input collection are passed iteratively to the decision. As the latter is NOT a collection in the example, it is my understanding there should be some form of aggregation(?).

I can understand how this should work for numerical values (e.g. "aggregate" by sum) however I am not clear of the aggregation method (is it always sum?). Furthermore, how should aggregation work if the output column of the decision contains strings?

Example: Two rules: "a"->"b", "c"->"d". Then an input collection {"a","c"} is passed. So the two outputs are "b", "d". As the decision is NOT a collection, we should not yield something like {"b","d"}, but should aggregate(?), yet, as stated, how to aggregate b,d?