Anomalies such as redundant, contradictory or deficient knowledge in a knowledge base indicate possible errors. Various methods for detecting such anomalies have been introduced, analyzed and applied in the past years, but they usually deal with rule-based systems. So far, little attention has been payed to the verification and validation of nonmonotonic knowledge bases, although there are good reasons to expect that such knowledge bases will be increasingly used in practical applications. This paper discusses how classical verification methods may be applied to detect some anomalies in nonmonotonic knowledge bases. These anomalies are first described in a formal way, and then generic verification methods to detect them are presented.