Discovering Recurring Anomalies in Text Reports Regarding Complex Space Systems

Abstract

Many existing complex space systems have a significant amount of historical maintenance and problem data bases that are stored in unstructured text forms. For some platforms, these reports may be encoded as scanned images rather than even searchable text. The problem that we address in this paper is the discovery of recurring anomalies and relationships between different problem reports that may indicate larger systemic problems. We will illustrate our techniques on data from discrepancy reports regarding software anomalies in the Space Shuttle. These free text reports are written by a number of different penp!e, thus the emphasis and wording varies considerably.