Validating the contribution of real world 
knowledge to the diagnostic performance of automated 
database design tools






diagnosis


Automated database design tools that employ 
knowledge-based systems technology have the capability of 
providing intelligent support to humans during the 
process of database analysis and design. However, 
the capacity of these tools to simulate 
the diagnostic capabilities of human designers when 
performing a design task by making use 
of their knowledge of the real world 
remains a question. Therefore, in recent years 
there have been a number of attempts 
to develop tools that are capable of 
exploiting such real-world knowledge. It has been 
claimed that the use of such knowledge 
has the potential to increase the diagnostic 
performance of automated database design tools. However, 
to date little if any formal exploration 
and validation of this claim has taken 
place. This paper presents the work on 
exploring and validating the implications of exploiting 
three approaches proposed to facilitate the use 
and exploitation of real-world knowledge to the 
aspects of diagnostic performance of database design 
tools. Results obtained have demonstrated that the 
improvement of certain aspects of the diagnostic 
performance have been achieved.