In the temporal reasoning, it is necessary to cope with incomplete knowledge since continuance or changes of occurrences usually depend on uncertain situations or have exceptions. Incomplete continuance of occurrences is usually treated by the default rule which assumes that occurrences can continue so long as they are consistent. Incomplete changes of occurrences can be treated by assuming and testing what changes can happen consistently. In this paper, we present the assumption-based temporal reasoning system VATS which deals with the above incompleteness. VATS has the following characteristics; (1) It selects a causal view from a causal view network in order to control a focus of attention in assumption-based temporal reasoning. A causal view is a kind of frame structure that consists of selected assumption formation rules and selected causal and temporal constraints for a given goal and premises. (2) It infers a hypothetical world which is represented in terms of a set of occurrences that are interrelated by causal and temporal constraints. Each occurrence has a temporal point or a temporal interval it occurs or continues. (3) Possible changes are assumed by the default assumption formation rules or the selective assumption formation rules. An assumption formative set is used for forming assumptions selectively. (4) A minimal set of minimal inconsistent environments is used for making consistency maintenance of hypothetical worlds efficient. It is also used for selecting more plausible hypothetical worlds by adding temporal constraints. This paper shows the occurrence-based hypothetical world representation and the view-guided assumption-based temporal reasoning algorism of VATS.