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A major phase in the construction of Knowledge-Based Systems (KBSs) is the Knowledge Acquisition stage. It involves acquiring knowledge from experts, books, examples and from other relevant sources. Until recently, researchers assumed a simplistic view of knowledge which required it being 'extracted' or 'mined' from experts. It is now clear that this simplistic view ignored the rich epistemological, cognitive and perceptual basis of what we refer to as knowledge. This thesis set about to address this problem. It identifies domain analysis as an early stage in the knowledge acquisition process and argues that it should capture the expert's perception of the domain, rather than the knowledge engineer's view of the expert's perception. It puts forward the thesis that metaphors are invaluable cognitive devices for perceiving and articulating domains. This idea has been postulated by several other researchers but never, until now, tested. This thesis prescribes a novel method for exploiting metaphors for knowledge acquisition. The method is based on Black's interaction view of metaphors which has been merged with Kelly's personal construct psychology. We have implemented a tool, DAKUM, based on this new method and evaluated the usefulness of metaphors for knowledge acquisition. We conclude that metaphors are useful for constructing a domain's functions and structure. However, we note that metaphors are only useful, when describing Juzzy domains; their use in describing relatively organised domains could often lead to confusion. Metaphorically speaking, we conclude that using metaphors is analogous to using a walking stick. The latter is only useful when it is needed; otherwise its use is often a hindrance.

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A considerable amount of work has been done in the field of verifying that computer programs fit their specifications. However, providing correct formal specifications is itself a fairly difficult and tedious task. Typically, people accept informal and incomplete descriptions of programs. These are used for "finding your way around" a large program, perhaps to identify troublesome parts. If formal correctness techniques are used at all, it will only be once suspect areas have been identified informally. This report presents a computer system that compares a LISP program with a description of the program written in a subset of English. The system interprets the English text; compares its interpretation with the code, using techniques concerned with superficial characteristics of the interpretation; investigates its comparison in detail using more formal techniques; and finally produces a documented version of the program, a brief report on how the specifications are implemented, and a database of detailed assertions about how the program and the specifications correspond.

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No description available.

No description available.

No description available.

No description available.