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P9613   Leon Moonen
        "Data flow analysis for reverse engineering"


Data flow analysis is a process for collecting run-time information about
data in programs without actually executing them. In this thesis, we focus
at the use of data flow analysis to support program understanding and
reverse engineering. Data flow analysis is beneficial for these
applications since the information obtained can be used to compute
relationships between data objects in programs. These relations, for
example, play a key role in the determination of a system's logical
components and their interaction.

The general support of program understanding and reverse engineering
requires the ability to analyze a variety of source languages and data flow
problems. This can be established by using a framework which facilitates
the specification and execution of data flow analysis algorithms. We will
present a flexible and generic software architecture for describing and
performing data flow analysis. All components of this framework and their
interaction are algebraically specified in ASF+SDF.