AbstractComparison of different approaches to expert system design for a given task, such as diagnosis, is difficult since they are eoften embodied in systems for domains with very different characteristics. It is a priori difficult to decide if a given difference in the approaches is necessitated by the differences in the domain. For example, it might be suggested that MYCIN's global and numeric uncertainty calculus is needed in domains such as MYCIN's, apparently characterized by a great deal of uncertainty in knowledge and data, while the approach of MDX, another medical system, which uses local combinations of qualitative probabilities only, may be too weak in such domains. In order to study the relationship between the domain characteristics and problem-solving approaches of the two systems, we constructed an MDX-like system for a subdomain of MYCIN and conducted a number of experiments on the resulting system. The results demonstrate that the MDX paradigm is effective in this domain and, additionally, offers knowledge engineering advantages along the dimension of debugging ease and system extensibility.