Distributed-system observation is foundational to understanding and controlling distributed computations. Existing tools for distributed-system observation are constrained in the size of computation that they can observe by three fundamental problems. They lack scalable information collection, scalable data-structures for storing and querying the information collected, and scalable information-abstraction schemes. This dissertation addresses the second of these prob- lems.

Abstract. Tool support is an important factor for efficient development of parallel programs. Due to different goals, target systems, and levels of abstraction, many specialized tools and environments have been developed. A contrary approach in the area of parallel program analysis is offered by DeWiz, which focuses on unified analysis functionality based on the event graph model. The desired analysis tasks are formulated as a set of graph filtering and transformation operations, which are implemented as independent analysis modules. The concrete analysis strategy is composed by placing these modules on arbitrary networked machines, arranging and interconnecting them. The resulting DeWiz system processes the data stream to extract useful information for program analysis. 1