Testing And Validation In Artificial Intelligence Programming
János Sztipanovits, S. Padalkar, C. Krishnamurthy, R. B. Purves · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1987
The paper describes a test and validation toolset developed for artificial intelligence programs. The basic premises of this method are: (1) knowledge bases have a strongly declarative character and represent mostly structural information about different domains, (2) the conditions for integrity, consistency and correctness can be transformed to structural properties of knowledge bases and (3) structural information and structural properties can be uniformly represented by graphs and checked by graph algorithms. The interactive test and validation environment have been implemented on a SUN workstation.