Fast online pointer analysis

Hirzel, Martin; Dincklage, Daniel von; Diwan, Amer; Hind, Michael

doi:10.1145/1216374.1216379

Cited by 48 publications

(34 citation statements)

References 79 publications

(66 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Livshits et al [33] proposed a static reflection resolution algorithm, which approximates the target of reflective calls as part of call graph construction, complemented by user provided specifications for reflective calls that rely on application input. Hirzel et al [22,21] presented an online version of Andersen's points-to analysis [2] that executes alongside the program, as an extension to the Jikes RVM [1], an open-source Java Research Virtual Machine. Thus the analysis has access to the new code as its loaded.…”

Section: Dynamic Featuresmentioning

confidence: 99%

Safe and efficient hybrid memory management for Java

Stancu

Wimmer

Brunthaler

et al. 2015

Proceedings of the 2015 International Symposium on Memory Management

View full text Add to dashboard Cite

Professor Michael Franz, Chair Java uses automatic memory management, usually implemented as a garbage-collected heap.That lifts the burden of manually allocating and deallocating memory, but it can incur significant runtime overhead and increase the memory footprint of applications. We propose a hybrid memory management scheme that utilizes region-based memory management to deallocate objects automatically on region exits. Static program analysis detects allocation sites that are safe for region allocation, i.e., the static analysis proves that the objects allocated at such a site are not reachable after the region exit. A regular garbage-collected heap is used for objects that are not region allocatable.The region allocation exploits the temporal locality of object allocation. Our analysis uses coarse-grain source code annotations to disambiguate objects with non-overlapping lifetimes, and maps them to different memory regions. Region-allocated memory does not require garbage collection as the regions are simply deallocated when they go out of scope. The region allocation technique is backed by a garbage collector that manages memory that is not region allocated.We provide a detailed description of the analysis, provide experimental results showing that as much as 78% of the memory is region allocatable and discuss how our hybrid memory management system can be implemented efficiently with respect to both space and time.xi

show abstract

Section: Dynamic Featuresmentioning

confidence: 99%

Safe and efficient hybrid memory management for Java

Stancu

Wimmer

Brunthaler

et al. 2015

Proceedings of the 2015 International Symposium on Memory Management

View full text Add to dashboard Cite

show abstract

“…The static analysis can run during the warm-up period of the application, so that the region information is available to the JIT compiler when it optimizes a method. Or the runtime system can perform the pointer analysis online during program execution as proposed by Hirzel et al [21]. Because of the explicitly marked memory regions, the static analysis does not need to analyze all Java code (e.g., the whole JDK).…”

Section: Region Analysis Operationmentioning

confidence: 99%

Safe and efficient hybrid memory management for Java

et al. 2015

View full text Add to dashboard Cite

Java uses automatic memory management, usually implemented as a garbage-collected heap. That lifts the burden of manually allocating and deallocating memory, but it can incur significant runtime overhead and increase the memory footprint of applications. We propose a hybrid memory management scheme that utilizes region-based memory management to deallocate objects automatically on region exits. Static program analysis detects allocation sites that are safe for region allocation, i.e., the static analysis proves that the objects allocated at such a site are not reachable after the region exit. A regular garbage-collected heap is used for objects that are not region allocatable. The region allocation exploits the temporal locality of object allocation. Our analysis uses coarse-grain source code annotations to disambiguate objects with non-overlapping lifetimes, and maps them to different memory scopes. Region-allocated memory does not require garbage collection as the regions are simply deallocated when they go out of scope. The region allocation technique is backed by a garbage collector that manages memory that is not region allocated. We provide a detailed description of the analysis, provide experimental results showing that as much as 78% of the memory is region allocatable and discuss how our hybrid memory management system can be implemented efficiently with respect to both space and time.

show abstract

“…Type masks are created before the propagation and are used for type filtering during the propagation [9]. The suitable type mask is determined based on type of the points-to set containing the bit-vector.…”

Section: Ranged Bit-vectorsmentioning

confidence: 99%

“…Previous works have implemented efficient and compact points-to sets which make the overall analysis more efficient [2]- [8]. Points-to sets which are represented based on bit-vectors [4], [5], [9] and points-to sets which are represented and manipulated based on BDD relations are shown to be more efficient [2], [3], [6], [7], [8], [10]. In this paper we utilize bit-vector representation of points-to sets.…”

Section: Introductionmentioning

confidence: 99%

Improving Bit-Vector Representation of Points-To Sets Using Class Hierarchy

Toussi¹,

Khademzadeh²

2013

IJCTE

View full text Add to dashboard Cite

Abstract-Points-to analysis is the problem of approximating run-time values of pointers statically or at compile-time. Points-to sets are used to store the approximated values of pointers during points-to analysis. Memory usage and running time limit the ability of points-to analysis to analyze large programs.To our knowledge, works which have implemented a bit-vector representation of points-to sets so far, allocates bits for each pointer without considering pointer's type. By considering the type, we are able to allocate bits only for a subset of all abstract objects which are of compatible type with the pointer's type and as a consequence improve the memory usage and running time. To achieve this goal, we number abstract objects in a way that all the abstract objects of a type and all of its sub-types are consecutive in order.Our most efficient implementation uses about 2.5× less memory than hybrid points-to set (default points-to set in Spark) and also improves the analysis time for sufficiently large programs.

show abstract

Fast online pointer analysis

Cited by 48 publications

References 79 publications

Safe and efficient hybrid memory management for Java

Safe and efficient hybrid memory management for Java

Safe and efficient hybrid memory management for Java

Improving Bit-Vector Representation of Points-To Sets Using Class Hierarchy

Contact Info

Product

Resources

About