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Journal articles on the topic 'Pointer Analysi'

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Author: Grafiati

Published: 11 March 2023

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1

Shields, Denis C., Andrew Collins, and Angela Marlow. "Coding of pointers in the segregation analysis program POINTER." Genetic Epidemiology 11, no. 4 (1994): 385–87. http://dx.doi.org/10.1002/gepi.1370110408.

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2

Matsumoto, Aki, D. S. Han, and Takao Tsuda. "Alias analysis of pointers in Pascal and Fortran 90: dependence analysis between pointer references." Acta Informatica 33, no. 2 (March 1996): 99–130. http://dx.doi.org/10.1007/s002360050037.

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3

Smaragdakis, Yannis, and George Balatsouras. "Pointer Analysis." Foundations and Trends® in Programming Languages 2, no. 1 (2015): 1–69. http://dx.doi.org/10.1561/2500000014.

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4

Hirzel, Martin, Daniel Von Dincklage, Amer Diwan, and Michael Hind. "Fast online pointer analysis." ACM Transactions on Programming Languages and Systems 29, no. 2 (April 2007): 11. http://dx.doi.org/10.1145/1216374.1216379.

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5

Zhu, Jianwen, and Silvian Calman. "Symbolic pointer analysis revisited." ACM SIGPLAN Notices 39, no. 6 (June 9, 2004): 145–57. http://dx.doi.org/10.1145/996893.996860.

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6

Peng-Sheng Chen, Yuan-Shin Hwang, R. D. C. Ju, and J. K. Lee. "Interprocedural probabilistic pointer analysis." IEEE Transactions on Parallel and Distributed Systems 15, no. 10 (October 2004): 893–907. http://dx.doi.org/10.1109/tpds.2004.56.

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7

Spoto, Fausto. "Precise null-pointer analysis." Software & Systems Modeling 10, no. 2 (October 2, 2009): 219–52. http://dx.doi.org/10.1007/s10270-009-0132-5.

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8

Heintze, Nevin, and Olivier Tardieu. "Demand-driven pointer analysis." ACM SIGPLAN Notices 36, no. 5 (May 2001): 24–34. http://dx.doi.org/10.1145/381694.378802.

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9

Hind, Michael, Michael Burke, Paul Carini, and Jong-Deok Choi. "Interprocedural pointer alias analysis." ACM Transactions on Programming Languages and Systems 21, no. 4 (July 1999): 848–94. http://dx.doi.org/10.1145/325478.325519.

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10

Wang, Shao-Chung, Lin-Ya Yu, Li-An Her, Yuan-Shin Hwang, and Jenq-Kuen Lee. "Pointer-Based Divergence Analysis for OpenCL 2.0 Programs." ACM Transactions on Parallel Computing 8, no. 4 (December 31, 2021): 1–23. http://dx.doi.org/10.1145/3470644.

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A modern GPU is designed with many large thread groups to achieve a high throughput and performance. Within these groups, the threads are grouped into fixed-size SIMD batches in which the same instruction is applied to vectors of data in a lockstep. This GPU architecture is suitable for applications with a high degree of data parallelism, but its performance degrades seriously when divergence occurs. Many optimizations for divergence have been proposed, and they vary with the divergence information about variables and branches. A previous analysis scheme viewed pointers and return values from functions as divergence directly, and only focused on OpenCL 1.x. In this article, we present a novel scheme that reports the divergence information for pointer-intensive OpenCL programs. The approach is based on extended static single assignment (SSA) and adds some special functions and annotations from memory SSA and gated SSA. The proposed scheme first constructs extended SSA, which is then used to build a divergence relation graph that includes all of the possible points-to relationships of the pointers and initialized divergence states. The divergence state of the pointers can be determined by propagating the divergence state of the divergence relation graph. The scheme is further extended for interprocedural cases by considering function-related statements. The proposed scheme was implemented in an LLVM compiler and can be applied to OpenCL programs. We analyzed 10 programs with 24 kernels, with a total analyzed program size of 1,306 instructions in an LLVM intermediate representation, with 885 variables, 108 branches, and 313 pointer-related statements. The total number of divergent pointers detected was 146 for the proposed scheme, 200 for the scheme in which the pointer was always divergent, and 155 for the current LLVM default scheme; the total numbers of divergent variables detected were 458, 519, and 482, respectively, with 31, 34, and 32 divergent branches. These experimental results indicate that the proposed scheme is more precise than both a scheme in which a pointer is always divergent and the current LLVM default scheme.

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11

Petri, Aspasia, and Efthymios Karabetsos. "Extreme output power emitted by commercial laser pointers in Greece: A solely local or a global issue?" Journal of Laser Applications 34, no. 2 (May 2022): 022025. http://dx.doi.org/10.2351/7.0000664.

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Although several countries have enacted legislation that prohibits the commercial distribution of laser pointers, high-power laser pointers are abundantly available on the market. The Greek Atomic Energy Commission (EEAE) investigated the compliance of laser pointers with the laser radiation safety limits in order to apply risk management actions in Greece. Compliance was assessed based on the laser pointer labeled data and in-house optical measurements. Laser pointers were purchased randomly from domestic physical marketplaces. Output power measurements revealed the risk of overexposure compared to the lasers' radiation safety limit values. Measured values also exceeded the output power values claimed on the laser pointer labels; hence, they may pose an unexpected more severe hazard than stated. Spectral analysis revealed an additional emission wavelength by the green laser pointers. All the inspected laser pointers declared “compliance with 21 CFR” and were labeled according to the U.S. 21 CFR 1040.1, although all consumer products available on the Greek market should comply with the relevant EU Directives, harmonized standards, and national legislation. These local findings adhere to a global issue—the unambiguous exposure of nonexpert users to high-power laser pointers that should not be commercially available. Overexposure to laser pointer radiation suppresses national borders as markets are not locally constrained, and laser technology continues to advance. The introduction of a universal laser safety language and a universal regulatory framework for laser pointers might facilitate product safety, international trade, and users' safety. EEAE runs social media campaigns to raise public awareness of laser pointer risks, using specifically designed infographics.

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12

Thiessen, Rei, and Ondřej Lhoták. "Context transformations for pointer analysis." ACM SIGPLAN Notices 52, no. 6 (September 14, 2017): 263–77. http://dx.doi.org/10.1145/3140587.3062359.

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13

Rugina, Radu, and Martin Rinard. "Pointer analysis for multithreaded programs." ACM SIGPLAN Notices 34, no. 5 (May 1999): 77–90. http://dx.doi.org/10.1145/301631.301645.

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14

Jianwen Zhu and S. Calman. "Context sensitive symbolic pointer analysis." IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems 24, no. 4 (April 2005): 516–31. http://dx.doi.org/10.1109/tcad.2005.844092.

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15

Horwitz, S., P. Pfeiffer, and T. Reps. "Dependence analysis for pointer variables." ACM SIGPLAN Notices 24, no. 7 (July 1989): 28–40. http://dx.doi.org/10.1145/74818.74821.

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16

Brauer, Jörg, Ralf Huuck, and Bastian Schlich. "Interprocedural Pointer Analysis in Goanna." Electronic Notes in Theoretical Computer Science 254 (October 2009): 65–83. http://dx.doi.org/10.1016/j.entcs.2009.09.060.

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17

Vivien, Frédéric, and Martin Rinard. "Incrementalized pointer and escape analysis." ACM SIGPLAN Notices 36, no. 5 (May 2001): 35–46. http://dx.doi.org/10.1145/381694.378804.

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18

Machiry, Aravind, John Kastner, Matt McCutchen, Aaron Eline, Kyle Headley, and Michael Hicks. "C to checked C by 3c." Proceedings of the ACM on Programming Languages 6, OOPSLA1 (December 8, 2022): 1–29. http://dx.doi.org/10.1145/3527322.

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Owing to the continued use of C (and C++), spatial safety violations (e.g., buffer overflows) still constitute one of today's most dangerous and prevalent security vulnerabilities. To combat these violations, Checked C extends C with bounds-enforced checked pointer types. Checked C is essentially a gradually typed spatially safe C - checked pointers are backwards-binary compatible with legacy pointers, and the language allows them to be added piecemeal, rather than necessarily all at once, so that safety retrofitting can be incremental. This paper presents a semi-automated process for porting a legacy C program to Checked C. The process centers on 3C, a static analysis-based annotation tool. 3C employs two novel static analysis algorithms - typ3c and boun3c - to annotate legacy pointers as checked pointers, and to infer array bounds annotations for pointers that need them. 3C performs a root cause analysis to direct a human developer to code that should be refactored; once done, 3C can be re-run to infer further annotations (and updated root causes). Experiments on 11 programs totaling 319KLoC show 3C to be effective at inferring checked pointer types, and experience with previously and newly ported code finds 3C works well when combined with human-driven refactoring.

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19

Hind, Michael, and Anthony Pioli. "Which pointer analysis should I use?" ACM SIGSOFT Software Engineering Notes 25, no. 5 (September 2000): 113–23. http://dx.doi.org/10.1145/347636.348916.

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20

Hardekopf, Ben, and Calvin Lin. "Semi-sparse flow-sensitive pointer analysis." ACM SIGPLAN Notices 44, no. 1 (January 21, 2009): 226–38. http://dx.doi.org/10.1145/1594834.1480911.

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21

Rugina, Radu, and Martin C. Rinard. "Pointer analysis for structured parallel programs." ACM Transactions on Programming Languages and Systems 25, no. 1 (January 2003): 70–116. http://dx.doi.org/10.1145/596980.596982.

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22

Liu, Bozhen, Jeff Huang, and Lawrence Rauchwerger. "Rethinking Incremental and Parallel Pointer Analysis." ACM Transactions on Programming Languages and Systems 41, no. 1 (March 2019): 1–31. http://dx.doi.org/10.1145/3293606.

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23

ÇEZİKTÜRK, Özlem. "CONTENT ANALYSIS OF STUDENTS' CONSTRUCTIONS OF EIGHT POINTED, TEN POINTED, AND TWELVE POINTED STARS." Journal of Academic Social Sciences 75, no. 75 (January 1, 2018): 244–54. http://dx.doi.org/10.16992/asos.13978.

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24

Abdulhadi, Zayid, and Walter Hengartner. "One Pointed Univalent Logharmonic Mappings." Journal of Mathematical Analysis and Applications 203, no. 2 (October 1996): 333–51. http://dx.doi.org/10.1006/jmaa.1996.0383.

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25

Li, Yue, Tian Tan, Anders Møller, and Yannis Smaragdakis. "Precision-guided context sensitivity for pointer analysis." Proceedings of the ACM on Programming Languages 2, OOPSLA (October 24, 2018): 1–29. http://dx.doi.org/10.1145/3276511.

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26

Zhang, Sean, Barbara G. Ryder, and William A. Landi. "Experiments with combined analysis for pointer aliasing." ACM SIGPLAN Notices 33, no. 7 (July 1998): 11–18. http://dx.doi.org/10.1145/277633.277635.

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27

Pearce, David J., Paul H. J. Kelly, and Chris Hankin. "Efficient field-sensitive pointer analysis of C." ACM Transactions on Programming Languages and Systems 30, no. 1 (November 2007): 4. http://dx.doi.org/10.1145/1290520.1290524.

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28

Salcianu, Alexandru, and Martin Rinard. "Pointer and escape analysis for multithreaded programs." ACM SIGPLAN Notices 36, no. 7 (July 2001): 12–23. http://dx.doi.org/10.1145/568014.379553.

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29

Guyer, Samuel Z., and Calvin Lin. "Error checking with client-driven pointer analysis." Science of Computer Programming 58, no. 1-2 (October 2005): 83–114. http://dx.doi.org/10.1016/j.scico.2005.02.005.

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30

Scholz, Berhard, Johann Blieberger, and Thomas Fahringer. "Symbolic pointer analysis for detecting memory leaks." ACM SIGPLAN Notices 34, no. 11 (November 1999): 104–13. http://dx.doi.org/10.1145/328691.328704.

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31

Das, Manuvir. "Unification-based pointer analysis with directional assignments." ACM SIGPLAN Notices 35, no. 5 (May 2000): 35–46. http://dx.doi.org/10.1145/358438.349309.

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32

Cheng, Ben-Chung, and Wen-Mei W. Hwu. "Modular interprocedural pointer analysis using access paths." ACM SIGPLAN Notices 35, no. 5 (May 2000): 57–69. http://dx.doi.org/10.1145/358438.349311.

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33

Da Silva, Jeff, and J. Gregory Steffan. "A probabilistic pointer analysis for speculative optimizations." ACM SIGOPS Operating Systems Review 40, no. 5 (October 20, 2006): 416–25. http://dx.doi.org/10.1145/1168917.1168908.

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34

Da Silva, Jeff, and J. Gregory Steffan. "A probabilistic pointer analysis for speculative optimizations." ACM SIGPLAN Notices 41, no. 11 (November 2006): 416–25. http://dx.doi.org/10.1145/1168918.1168908.

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35

Da Silva, Jeff, and J. Gregory Steffan. "A probabilistic pointer analysis for speculative optimizations." ACM SIGARCH Computer Architecture News 34, no. 5 (October 20, 2006): 416–25. http://dx.doi.org/10.1145/1168919.1168908.

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36

Lyde, Steven, William E. Byrd, and Matthew Might. "Control-flow analysis of dynamic languages via pointer analysis." ACM SIGPLAN Notices 51, no. 2 (May 11, 2016): 54–62. http://dx.doi.org/10.1145/2936313.2816712.

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37

El Abbadi, Nidhal. "New Algorithm for Text in Text Steganography." Journal of Al-Rafidain University College For Sciences ( Print ISSN: 1681-6870 ,Online ISSN: 2790-2293 ), no. 2 (October 26, 2021): 99–112. http://dx.doi.org/10.55562/jrucs.v23i2.483.

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Steganography is a technique to hide secret information in some other data (we call it a cover) without leaving any apparent evidence of data alteration. All of the traditional steganographic techniques have limited information- hiding capacity. They can hide only 10% (or less) of the data amounts of the cover. While much of the recent research in steganography has been on hiding data in images, many of the solutions that for images are more complicated when applied to natural language text as a cover medium. Many approaches to steganalysis attempt to detect statistical anomalies in cover data which predict the presence of hidden information. Natural language cover texts must not only pass the statistical muster of automatic analysis, but also the minds of human readers. This paper present a new algorithm to hide a large amount of text in cover text without effecting the cover, by using many types of pointers ( which are characters can interpreter as invisible character, or as apart of cover. Pointers used as single pointer or set of pointer to represent new single pointer. In this algorithm we can hide more than 40% of the data amounts of the cover.

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38

Liu, Xia, Ming Lei, Hu Wei Liu, Yin Cao, and Xiao Hong Gao. "Risk Analysis of Quality and Safety for Laser Pointer with Remote Control." Advanced Materials Research 968 (June 2014): 263–66. http://dx.doi.org/10.4028/www.scientific.net/amr.968.263.

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Multimedia teaching and lecturing have been widely used nowadays, and then the technology of laser pointer with remote control appears in order to satisfy the requirements. The radiation power of some laser pointers is large, which may be lead to impaired eyes due to improper use. The hazard of laser radiation was analyzed. The standards, laws and regulations of the domestic and foreign were compared. Some suggestions and measures of perfecting the relative standards, strengthening consumers' education and industry rectification were provided.

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39

Chase, David, Mark Wegman, and F. Ken Zadeck. "Analysis of pointers and structures." ACM SIGPLAN Notices 39, no. 4 (April 2004): 343–59. http://dx.doi.org/10.1145/989393.989429.

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40

Chase, David R., Mark Wegman, and F. Kenneth Zadeck. "Analysis of pointers and structures." ACM SIGPLAN Notices 25, no. 6 (June 1990): 296–310. http://dx.doi.org/10.1145/93548.93585.

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41

Junjie Wang, Xiaohong Li, Bobo Yan, and Zhiyong Feng. "Pointer Analysis Based Vulnerability Detection for Browser Extension." International Journal of Digital Content Technology and its Applications 6, no. 1 (January 31, 2012): 488–95. http://dx.doi.org/10.4156/jdcta.vol6.issue1.59.

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42

Whaley, John, and Martin Rinard. "Compositional pointer and escape analysis for Java programs." ACM SIGPLAN Notices 34, no. 10 (October 1999): 187–206. http://dx.doi.org/10.1145/320385.320400.

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43

Yong, Suan Hsi, Susan Horwitz, and Thomas Reps. "Pointer analysis for programs with structures and casting." ACM SIGPLAN Notices 34, no. 5 (May 1999): 91–103. http://dx.doi.org/10.1145/301631.301647.

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44

Landi, William, Barbara G. Ryder, and Sean Zhang. "Interprocedural modification side effect analysis with pointer aliasing." ACM SIGPLAN Notices 28, no. 6 (June 1993): 56–67. http://dx.doi.org/10.1145/173262.155096.

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45

Sui, Yulei, Xiaokang Fan, Hao Zhou, and Jingling Xue. "Loop-Oriented Pointer Analysis for Automatic SIMD Vectorization." ACM Transactions on Embedded Computing Systems 17, no. 2 (April 26, 2018): 1–31. http://dx.doi.org/10.1145/3168364.

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46

Venet, A. "Automatic analysis of pointer aliasing for untyped programs." Science of Computer Programming 35, no. 2-3 (November 1999): 223–48. http://dx.doi.org/10.1016/s0167-6423(99)00012-x.

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47

Huang, Bo, Binyu Zang, Jing Li, and Chuanqi Zhu. "A new approach to pointer analysis for assignments." Journal of Computer Science and Technology 16, no. 3 (May 2001): 242–50. http://dx.doi.org/10.1007/bf02943202.

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48

Wilson, Robert P., and Monica S. Lam. "Efficient context-sensitive pointer analysis for C programs." ACM SIGPLAN Notices 30, no. 6 (June 1995): 1–12. http://dx.doi.org/10.1145/223428.207111.

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49

Ellyana, Rossy Lydia, and I. Wayan Angga Wijaya Kusuma. "Penentuan Indeks Bias Kaca Berdasarkan Pola Interferensi Cahaya Laser Terhambur Menggunakan Cermin Datar “Berdebu”." Jurnal Teori dan Aplikasi Fisika 7, no. 2 (July 31, 2019): 169–78. http://dx.doi.org/10.23960/jtaf.v7i2.2150.

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Experiment on Interference Pattern of Laser Light Scattered Analysis using a "Dusty" Plane Mirror aims to determine the glass refractive index value. The dust samples used in this experiment are baby powder, chalk, rice flour, wood powder and beauty powder. The dust samples sprinkled over a clean mirror, so it will produce an interference pattern that can be seen on the screen. The results of the interference pattern are circular because the screen is perforated with a diameter of 0.01 m. Dust particle sample variation only affects the brightness level of interference patterns. Analysis of interference patterns using red laser pointers or green laser pointers will get the brightest interference patterns when using baby powder compared to other dust samples. Based on the resulting interference pattern, the refractive index value of the glass using a red laser pointer is 1.62 ± 0.04 and the weighted average value of the glass refractive index is 1.68 ± 0.02, whereas the refractive index value of glass using a green laser pointer is 1.74 ± 0.07 and the weighted average value of the refractive index of the glass is 1.79 ± 0.02

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50

Li, Yajun. "Ruled surfaces generated by Risley prism pointers: I. Pointing accuracy evaluation and enhancement based on a structural analysis of the scan field inside the pointer." Journal of the Optical Society of America A 38, no. 12 (November 29, 2021): 1884. http://dx.doi.org/10.1364/josaa.435621.

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