A Framework for Partial Data Flow Analysis

Although data pow analysis was first developed for use in compilers, i t s usefulness is now recognized in many software tools. Because of its compiler origins, the computation of data pow for software tools is based on the traditional exhaustive data flow framework. However, although this framework is useful for computing data pow for compilers, it is not the most appropriate for sofsware tools, particularly those used in the maintenance stage. In maintenance, testing and debugging is typically performed in response to program changes. As such, the data pow required is demand driven from the changed program points. Rather than compute the data flow exhaustively using the traditional data flow framework, we present a framework f o r partial analysis. The framework includes a specification language enabling the specification of the demand driven data flow desired by a user. From the specification, a partial analysis algorithm is automatically generated using an L-attributed definition for the grammar of the specification language. A specification of a demand driven data pow problem expresses characteristics that define the kind of traversal needed in the partial analysis and the type of dependencies t o be captured. The partial analyses algorithms are eficient in that only as much of the program is analyzed as actually needed, thus reducing the time and space requirements over exhaustively computing the da ta f low information. The algorithms are shown to be useful when debugging and testing programs during maintenance.