Synectics is one of several techniques used to enhance brainstorming by taking a more active role and introducing metaphor and structure into the process. It is unclear at what level of specificity this should be formulated as a pattern. This thesis reviews recent computational as well as experimental work on analogical reasoning based on synectics. New results regarding information processing of analogical reasoning stages, major computational models and recent attempts to compare these models are reviewed. Computational models are also discussed in the computational as well as cognitive psychology perspectives. Future directions in analogical reasoning research are proposed. The following import is the need to accommodate the typology and normal assessment in the concrete circumstances where actual reasoning and problem solving take place. In order to get to this end, we used computational models by Thagard who take the stand of ‘Computational Philosophy of Science’, which assumes ‘Weak AI’ to explicate what constitute the very pecularity of Analogical Reasoning.