The ways that the methods of data flow analysis can be applied to improve software reliability are described. There is also a review of the basic terminology from graph theory and from data flow analysis in global program optimization. The notation of regular expressions is used to describe actions on data for sets of paths. These expressions provide the basis of a classification scheme for data flow which represents patterns of data flow along paths within subprograms and along paths which cross subprogram boundaries. Fast algorithms, originally introduced for global optimization, are described and it is shown how they can be used to implement the classification scheme. It is then shown how these same algorithms can also be used to detect the presence of data flow anomalies which are symptomatic of programming errors. Finally, some characteristics of and experience with DAVE, a data flow analysis system embodying some of these ideas, are described.

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This paper describes DAVE, a system for analysing Fortran programs. DAVE is capable of detecting the symptoms of a wide variety of errors In programs, as well as assuring the absence of these errors. In addition, DAVE exposes and documents subtle data relations and flows within programs. The central analytic procedure used is a depth first search. DAVE itself is written in Fortran. Its implementation at the University of Colorado and some early experience are described.