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Importance of heap specialization in pointer analysis
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Source Workshop on Program Analysis for Software Tools and Engineering archive
Proceedings of the 5th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering table of contents
Washington DC, USA
SESSION: Pointer analysis table of contents
Pages: 43 - 48  
Year of Publication: 2004
ISBN:1-58113-910-1
Authors
Erik M. Nystrom  University of Illinois, Urbana-Champaign
Hong-Seok Kim  University of Illinois, Urbana-Champaign
Wen-mei W. Hwu  University of Illinois, Urbana-Champaign
Sponsors
SIGPLAN: ACM Special Interest Group on Programming Languages
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 4,   Downloads (12 Months): 36,   Citation Count: 5
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ABSTRACT

Specialization of heap objects is critical for pointer analysis to effectively analyze complex memory activity. This paper discusses heap specialization with respect to call chains. Due to the sheer number of distinct call chains, exhaustive specialization can be cumbersome. On the other hand, insufficient specialization can miss valuable opportunities to prevent spurious data flow, which results in not only reduced accuracy but also increased overhead.In determining whether further specialization will be fruitful, an object's escape information can be exploited. From empirical study, we found that restriction based on escape information is often, but not always, sufficient at prohibiting the explosive nature of specialization.For in-depth case study, four representative benchmarks are selected. For each benchmark, we vary the degree of heap specialization and examine its impact on analysis results and time. To provide better visibility into the impact, we present the points-to set and pointed-to-by set sizes in the form of histograms.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Lars O. Andersen. Program Analysis and Specialization for the C Programming Language. Ph.D thesis, DIKU, Unversity of Copenhagen, 1994.
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Chris Lattner and Vikram Adve. Data Structure Analysis: A Fast and Scalable Context-Sensitive Heap Analysis. Technical Report, CS Dept., University of Illinois. 2003.
 
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Collaborative Colleagues:
Erik M. Nystrom: colleagues
Hong-Seok Kim: colleagues
Wen-mei W. Hwu: colleagues

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