Bidirectional data flow analysis for type inferencing

Autor:	Dhananjay M. Dhamdhere, Uday P. Khedker, Alan Mycroft
Rok vydání:	2003
Předmět:	Computer Programming Languages Computer Networks and Communications Computer science Theorem Proving Type (model theory) computer.software_genre Constraint (information theory) Data flow diagram Program Compilers Constraint Theory Data mining computer Software Data-flow analysis
Zdroj:	Computer Languages, Systems & Structures. 29:15-44
ISSN:	1477-8424
DOI:	10.1016/s1477-8424(03)00012-5
Popis:	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. © Elsevier
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d2ebaaa162d65668d5013b7e6d3e638e https://doi.org/10.1016/s1477-8424(03)00012-5 Zobrazit plný text záznamu Full Text from ScienceDirect