Bidirectional data flow analysis for type inferencing

Authors:
Uday P. Khedker;Dhananjay M. Dhamdhere;Alan Mycroft
Affiliations:
Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Bombay, India;Department of Computer Science and Engineering, Indian Institute of Technology Bombay, Bombay, India;Computer Laboratory, University of Cambridge, Cambridge, UK
Venue:
Computer Languages, Systems and Structures
Year:
2003

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Abstract

Tennenbaum's data flow analysis based formulation of type inferencing is termed bidirectional in the ''Dragon Book''; however, it fails to qualify as a formal data flow framework and is not amenable to complexity analysis. Further, the types discovered are imprecise. Here, we define a formal data flow framework (based on bidirectional data flow analysis) which discovers more precise type information and is amenable to complexity analysis. We compare data flow analyses with the more general constraint-based analyses and observe that data flow analyses represent program analyses without unbounded auxiliary store. We show that if unlimited auxiliary store is allowed then no data flow analysis would need more than two passes; if auxiliary store is disallowed then type inferencing requires bidirectional data flow analysis.