Software measurement is an essential infrastructure for the improvement of software quality and productivity. However, the successful planning of software measurement requires, in practice, a significant amount of effort and expertise. Costs can be reduced and the quality of measurement can be improved by reusing experiences gathered from past measurement programs within an organization. This thesis develops a general framework for the operationalization of the reuse of measurement plans and associated knowledge and experiences. This includes the development of a methodology for the systematic reuse of experiences extending the Goal/Question/Metric approach and the development and prototypical implementation of a Corporate Memory Management System based on the Experience Factory approach, which enables the continuous collection of experiences from measurement programs in an organization, the packaging of those experiences in a reusable form, their integration and storage into a Corporate Memory, and the supply of useful experiences on demand when planning new measurement programs. Therefore, techniques from the area of Artificial Intelligence, such as Case-Based Reasoning, are adapted and integrated. First results of an empirical evaluation of the approach provide indications for its positive impact on the efficiency and effectiveness of software measurement planning.