Alias analysis for optimization of dynamic languages

Dynamic languages such as Python allow programs to be written more easily using high-level constructs such as comprehensions for queries and using generic code. Efficient execution of programs then requires powerful optimizations-incrementalization of expensive queries and specialization of generic code. Effective incrementalization and specialization of dynamic languages require precise and scalable alias analysis. This paper describes the development and experimental evaluation of a may-alias analysis for a full dynamic objectoriented language, for program optimization by incrementalization and specialization. The analysis is flow-sensitive; we show that this is necessary for effective optimization of dynamic languages. It uses precise type analysis and a powerful form of context sensitivity, called trace sensitivity, to further improve analysis precision. It uses a compressed representation to significantly reduce the memory used by flowsensitive analyses. We evaluate the effective...

• Type: Journal
• Year: 2010
• Where: DLS
• Authors: Michael Gorbovitski, Yanhong A. Liu, Scott D. Stoller, Tom Rothamel, K. Tuncay Tekle
• Keywords: Analysis, DLS 2010, Dynamic Languages, Generic Code, Languages