Better static memory management: improving region-based analysis of higher-order languages
PLDI '95 Proceedings of the ACM SIGPLAN 1995 conference on Programming language design and implementation
Region-based memory management
Information and Computation
A region-based memory manager for prolog
Proceedings of the 2nd international symposium on Memory management
Region-based memory management in cyclone
PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
Principles of Program Analysis
Principles of Program Analysis
Practical Aspects for a Working Compile Time Garbage Collection System for Mercury
Proceedings of the 17th International Conference on Logic Programming
On Enabling the WAM with Region Support
ICLP '02 Proceedings of the 18th International Conference on Logic Programming
A direct approach to control-flow sensitive region-based memory management
Proceedings of the 3rd ACM SIGPLAN international conference on Principles and practice of declarative programming
A Retrospective on Region-Based Memory Management
Higher-Order and Symbolic Computation
Region analysis and transformation for Java programs
Proceedings of the 4th international symposium on Memory management
Runtime support for region-based memory management in Mercury
Proceedings of the 7th international symposium on Memory management
Path-sensitive region analysis for mercury programs
PPDP '09 Proceedings of the 11th ACM SIGPLAN conference on Principles and practice of declarative programming
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Region-based memory management is a form of compile-time memory management, well-known from the functional programming world. This paper describes a static region analysis for the logic programming language Mercury. We use region points-to graphs to model the partitioning of the memory used by a program into separate regions. The algorithm starts with a region points-to analysis that determines the different regions in the program. We then compute the liveness of the regions by using an extended live variable analysis. Finally, a program transformation adds region annotations to the program for region support. These annotations generate data for a region simulator that generates reports on the memory behaviour of region-annotated programs. Our approach obtains good memory consumption for several benchmark programs; for some of them it achieves optimal memory management.