Recent research suggests that the abilities of a knowledge-based system (KBS) depend in part on the amount of explicit knowledge it has about the way it is designed . This knowledge is often called design knowledge because it reflects design decisions that a KBS developer makes regarding what ontologies to embody in the system , what solution strategies to apply , what system architecture to use , etc . This paper examines one type of design knowledge pertaining to the structure underlying the solutions a KBS produces . (For example , in medical diagnosis , the output might be just a disease name , but the solution is actually a causal argument that the system implicitly constructs to find out how the disease came about . ) We define this type of design knowledge , show how it can be represented , and explain how it can be used in problem solving to make the structure underlying solutions explicit . Subsequently , we also present and illustrate new avenues that the availability and use of the design knowledge discussed open with respect to the ability to build KBSs that possess strong explanation capabilities , are easier to maintain , support knowledge reuse , and of fer more robustness in problem solving .