Building software from components, rather than writing the code from scratch has several advantages, including reduced time to market and more efficient resource usage. However, component based development without consideration of all the risks and limitations involved may give unpredictable results, such as the failure of a system when a component is used in an environment for which it was not originally designed. One of the basic problems when developing component-based systems is that it is difficult to keep track of components and their interrelationships. This is particularly problematic when upgrading components. One way to maintain control over upgrades is to use component identification and dependency analysis. These are well known techniques for managing system configurations during development, but are rarely applied in managing run-time dependencies. The main contribution of this thesis is to show how Configuration Management (CM) principles and methods can be applied to component-based systems. This thesis presents a method for analysing dependencies between components. The method predicts the influence of a component update by identifying the components in a system and constructing a graph describing their dependencies. Knowledge of the possible influences of an update is important, since it can be used to limit the scope of testing and be a basis for evaluating the potential damage of the update. The dependency graphs can also be used to facilitate maintenance by identifying differences between configurations, e.g., making it possible to recognise any deviations from a functioning reference configuration. For evaluation of the method, a prototype tool which explores dependencies and stores them under version control has been developed. The prototype has been used for partial analysis of the Windows 2000 platform. Preliminary experiments indicate that most components have only a few dependencies. The method has thus given an indication that the analysis of the effects of component updates may not be as difficult as might be expected.