Heap reference analysis using access graphs

Khedker, Uday P.; Sanyal, Amitabha

doi:10.1145/1290520.1290521

Cited by 37 publications

(12 citation statements)

References 41 publications

(55 reference statements)

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“…In contrast to these two works, our bottom-up technique addresses aliasing by predicating the results of local analysis on dangerous alias sets. Khedker et al [21] also find SAPs to aid garbage collection. They use a traditional dataflow analysis that is only intra-procedural.…”

Section: Related Workmentioning

confidence: 99%

Efficient bottom-up heap analysis for symbolic path-based data access summaries

Matosevic

Abdelrahman

2012

Proceedings of the Tenth International Symposium on Code Generation and Optimization

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We propose a heap analysis for extracting data access summaries based on symbolic access paths (SAPs) of methods in object-oriented languages. The analysis takes advantage of the insight that typical programs access dynamic data structures in regular manners. We combine this insight with a bottom-up approach that computes a local summary for each basic block, loop, and method in the program, which is then encapsulated into an abstract block in order to efficiently handle the higher levels of the analysis. We solve the problem of the dependence of local analysis results on the global heap aliasing by inferring the sets of aliases on which the correctness of the local results is predicated. Experimental evaluation for Java shows that for typical programs that use dynamic data structures, our analysis runs in a fast single pass and produces useful results.

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Section: Related Workmentioning

confidence: 99%

Efficient bottom-up heap analysis for symbolic path-based data access summaries

Matosevic

Abdelrahman

2012

Proceedings of the Tenth International Symposium on Code Generation and Optimization

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“…[20] presents a liveness analysis and uses the results for inserting nullifying statements in Java programs. In [29], temporal properties like liveness are checked against an automaton modeling heap accesses.…”

Section: Related Workmentioning

confidence: 99%

Liveness-based garbage collection for lazy languages

Kumar

Sanyal

2016

Proceedings of the 2016 ACM SIGPLAN International Symposium on Memory Management

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We consider the problem of reducing the memory required to run lazy first-order functional programs. Our approach is to analyze programs for liveness of heap-allocated data. The result of the analysis is used to preserve only live data-a subset of reachable data-during garbage collection. The result is an increase in the garbage reclaimed and a reduction in the peak memory requirement of programs. While this technique has already been shown to yield benefits for eager first-order languages, the lack of a statically determinable execution order and the presence of closures pose new challenges for lazy languages. These require changes both in the liveness analysis itself and in the design of the garbage collector.To show the effectiveness of our method, we implemented a copying collector that uses the results of the liveness analysis to preserve live objects, both evaluated and closures. Our experiments confirm that for programs running with a liveness-based garbage collector, there is a significant decrease in peak memory requirements. In addition, a sizable reduction in the number of collections ensures that in spite of using a more complex garbage collector, the execution times of programs running with liveness and reachability-based collectors remain comparable.

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“…We initially developed this framework in order to implement heap reference analysis [6] using Soot, because it could not be encoded as an IFDS/IDE problem. However, even with our general framework, performing whole-program analysis turned out to be infeasible due to a large number of interprocedural paths arising from conservative assumptions for targets of virtual calls.…”

Section: The Role Of Call Graphsmentioning

confidence: 99%

Interprocedural data flow analysis in Soot using value contexts

Padhye

Khedker

2013

Proceedings of the 2nd ACM SIGPLAN International Workshop on State of the Art in Java Program Analysis

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An interprocedural analysis is precise if it is flow sensitive and fully context-sensitive even in the presence of recursion. Many methods of interprocedural analysis sacrifice precision for scalability while some are precise but limited to only a certain class of problems.Soot currently supports interprocedural analysis of Java programs using graph reachability. However, this approach is restricted to IFDS/IDE problems, and is not suitable for general data flow frameworks such as heap reference analysis and points-to analysis which have non-distributive flow functions.We describe a general-purpose interprocedural analysis framework for Soot using data flow values for context-sensitivity. This framework is not restricted to problems with distributive flow functions, although the lattice must be finite. It combines the key ideas of the tabulation method of the functional approach and the technique of value-based termination of call string construction.The efficiency and precision of interprocedural analyses is heavily affected by the precision of the underlying call graph. This is especially important for object-oriented languages like Java where virtual method invocations cause an explosion of spurious call edges if the call graph is constructed naively. We have instantiated our framework with a flow and context-sensitive points-to analysis in Soot, which enables the construction of call graphs that are far more precise than those constructed by Soot's SPARK engine.

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Heap reference analysis using access graphs

Cited by 37 publications

References 41 publications

Efficient bottom-up heap analysis for symbolic path-based data access summaries

Efficient bottom-up heap analysis for symbolic path-based data access summaries

Liveness-based garbage collection for lazy languages

Interprocedural data flow analysis in Soot using value contexts

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