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Journal articles on the topic 'Alias analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 14 February 2022

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1

Diwan, Amer, Kathryn S. McKinley, and J. Eliot B. Moss. "Type-based alias analysis." ACM SIGPLAN Notices 33, no. 5 (1998): 106–17. http://dx.doi.org/10.1145/277652.277670.

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2

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

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3

Ohata, Fumiaki, Kazuhiro Kondou, and Katsuro Inoue. "Alias analysis method for object-oriented programs using alias flow graphs." Systems and Computers in Japan 35, no. 4 (2004): 49–59. http://dx.doi.org/10.1002/scj.1231.

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4

Ruf, Erik. "Context-insensitive alias analysis reconsidered." ACM SIGPLAN Notices 30, no. 6 (1995): 13–22. http://dx.doi.org/10.1145/223428.207112.

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5

Pang, Long, Xiao Hong Su, Pei Jun Ma, and Ling Ling Zhao. "Layered Region Based Flow-Sensitive Demand-Driven Alias Analysis." Applied Mechanics and Materials 577 (July 2014): 917–20. http://dx.doi.org/10.4028/www.scientific.net/amm.577.917.

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The pointer alias is indispensable for program analysis. Comparing to point-to set, it’s more efficient to formulate the alias as the context free language (CFL) reachability problem. However, the precision is limited to flow-insensitivity. To solve this problem, we propose a flow sensitive, demand-driven analysis algorithm for answering may-alias queries. First the partial single static assignment is used to discriminate the address-taken pointers. Then the order of control flow is encoded in the level linearization code to ease comparison. Finally, the query of alias in demand driven is conv

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6

Zheng, Xin, and Radu Rugina. "Demand-driven alias analysis for C." ACM SIGPLAN Notices 43, no. 1 (2008): 197–208. http://dx.doi.org/10.1145/1328897.1328464.

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7

Deutsch, Alain. "Interprocedural may-alias analysis for pointers." ACM SIGPLAN Notices 29, no. 6 (1994): 230–41. http://dx.doi.org/10.1145/773473.178263.

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8

Zhang, Qirun, Xiao Xiao, Charles Zhang, Hao Yuan, and Zhendong Su. "Efficient subcubic alias analysis for C." ACM SIGPLAN Notices 49, no. 10 (2014): 829–45. http://dx.doi.org/10.1145/2714064.2660213.

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9

Lu, Yu-Min, and Peng-Sheng Chen. "Probabilistic Alias Analysis of Executable Code." International Journal of Parallel Programming 39, no. 6 (2010): 663–93. http://dx.doi.org/10.1007/s10766-010-0157-y.

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10

Mahmoudi, Elham, Fatemeh Azizmohammadi, and Hamedreza Kohzadi. "A Postmodern Historiographical Analysis of Alias Grace." Anthropologist 17, no. 2 (2014): 633–38. http://dx.doi.org/10.1080/09720073.2014.11891472.

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11

Gorbovitski, Michael, Yanhong A. Liu, Scott D. Stoller, Tom Rothamel, and Tuncay K. Tekle. "Alias analysis for optimization of dynamic languages." ACM SIGPLAN Notices 45, no. 12 (2010): 27–42. http://dx.doi.org/10.1145/1899661.1869635.

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12

Mayer, Herbert G., and Michael Wolfe. "Interprocedural alias analysis: Implementation and empirical results." Software: Practice and Experience 23, no. 11 (1993): 1201–33. http://dx.doi.org/10.1002/spe.4380231103.

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13

Asăvoae, Irina Măriuca. "Abstract Semantics for Alias Analysis in K." Electronic Notes in Theoretical Computer Science 304 (June 2014): 97–110. http://dx.doi.org/10.1016/j.entcs.2014.05.005.

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14

LAYTON, ROBERT, PAUL A. WATTERS, and RICHARD DAZELEY. "Authorship analysis of aliases: Does topic influence accuracy?" Natural Language Engineering 21, no. 4 (2013): 497–518. http://dx.doi.org/10.1017/s1351324913000272.

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AbstractAliasesplay an important role in online environments by facilitating anonymity, but also can be used to hide the identity of cybercriminals. Previous studies have investigated this alias matching problem in an attempt to identify whether two aliases are shared by an author, which can assist with identifying users. Those studies create their training data by randomly splitting the documents associated with an alias into two sub-aliases. Models have been built that can regularly achieve over 90% accuracy for recovering the linkage between these ‘random sub-aliases’. In this paper, random

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15

Marx, Delia I. S., and Phyllis G. Frankl. "Path-sensitive alias analysis for data flow testing." Software Testing, Verification and Reliability 9, no. 1 (1999): 51–73. http://dx.doi.org/10.1002/(sici)1099-1689(199903)9:1<51::aid-stvr177>3.0.co;2-u.

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16

Goyal, Deepak. "Transformational Derivation of an Improved Alias Analysis Algorithm." Higher-Order and Symbolic Computation 18, no. 1-2 (2005): 15–49. http://dx.doi.org/10.1007/s10990-005-7005-6.

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17

Tao, Yang, Gang Hu, Bingnan Hou, Zhiping Cai, Jing Xia, and Cheang Chak Fong. "An Alias Resolution Method based on Delay Sequence Analysis." Computers, Materials & Continua 63, no. 3 (2020): 1433–43. http://dx.doi.org/10.32604/cmc.2020.09850.

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18

Rinetzky, N., G. Ramalingam, M. Sagiv, and E. Yahav. "On the complexity of partially-flow-sensitive alias analysis." ACM Transactions on Programming Languages and Systems 30, no. 3 (2008): 1–28. http://dx.doi.org/10.1145/1353445.1353447.

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19

Horwitz, Susan. "Precise flow-insensitive may-alias analysis is NP-hard." ACM Transactions on Programming Languages and Systems 19, no. 1 (1997): 1–6. http://dx.doi.org/10.1145/239912.239913.

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20

Li, Rui, Bangyin Liu, Shanxu Duan, Changyue Zou, and Ling Jiang. "Analysis and Suppression of Alias in Digitally Controlled Inverters." IEEE Transactions on Industrial Informatics 10, no. 1 (2014): 655–65. http://dx.doi.org/10.1109/tii.2013.2279498.

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21

Späth, Johannes, Karim Ali, and Eric Bodden. "IDE al : efficient and precise alias-aware dataflow analysis." Proceedings of the ACM on Programming Languages 1, OOPSLA (2017): 1–27. http://dx.doi.org/10.1145/3133923.

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22

Chatterjee, Krishnendu, Bhavya Choudhary, and Andreas Pavlogiannis. "Optimal Dyck reachability for data-dependence and alias analysis." Proceedings of the ACM on Programming Languages 2, POPL (2018): 1–30. http://dx.doi.org/10.1145/3158118.

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23

Xu, Qin, Kang Nai, Shun Liu, Chris Karstens, Travis Smith, and Qingyun Zhao. "Improved Doppler Velocity Dealiasing for Radar Data Assimilation and Storm-Scale Vortex Detection." Advances in Meteorology 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/562386.

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The Doppler velocity dealiasing technique based on alias-robust VAD and variational (AR-Var) analyses developed at the National Severe Storms Laboratory for radar data quality control and assimilation is further improved in its two-step procedures: the reference check in the first step and the continuity check in the second step. In the first step, the alias-robust variational analysis is modified adaptively and used in place of the alias-robust velocity-azimuth display (VAD) analysis for all scan modes (rather than solely the WSR-88D volume coverage pattern 31 with the Nyquist velocityvNreduc

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24

Cui, Wei Ping, and Zhen Yu. "Application of Wavelet Algorithm in Spectral Analysis." Applied Mechanics and Materials 380-384 (August 2013): 1633–36. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1633.

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The purpose of this paper is combined with the advantages of wavelet transform and FFT, using wavelet transform to change the signal decomposition, and the use of FFT and filter for the reconstructed signal to decompose the signal and extract the different frequency components. In processing, we find that there is frequency alias in sub-band reconstruction which is caused by Mallat algorithm. In this article, we offer a solution of this problem.

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25

Smith, C. C., J. F. Dahl, and R. Joe Thornhill. "The Duality of Leakage and Aliasing and Improved Digital Spectral Analysis Techniques." Journal of Dynamic Systems, Measurement, and Control 118, no. 4 (1996): 741–47. http://dx.doi.org/10.1115/1.2802351.

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When processing, recording, and analyzing continuous, analog signals or functions with a digital computer, information is lost when the signals are converted to digital form. When signals are sampled in one domain (time or frequency), the loss of information is characterized as aliasing in the other (frequency or time, respectively) domain. When a signal or function is truncated in one domain, the information loss is characterized as leakage in the other domain. It is shown that because of the dual nature of leakage and aliasing, that leakage in one domain reduces aliasing in the other domain

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26

Xu, Qin, and Kang Nai. "An Adaptive Dealiasing Method Based on Variational Analysis for Radar Radial Velocities Scanned with Small Nyquist Velocities." Journal of Atmospheric and Oceanic Technology 29, no. 12 (2012): 1723–29. http://dx.doi.org/10.1175/jtech-d-12-00145.1.

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Abstract Previous velocity–azimuth display (VAD)-based methods of dealiasing folded radial velocities have relied heavily on the VAD uniform-wind assumption and, thus, can fail when the uniform-wind assumption becomes poor around azimuthal circles in a vertical layer and the Nyquist velocity is small (≤12 m s−1). By using the two-step, alias-robust variational (AR-Var) analysis in place of the alias-robust VAD (AR-VAD) analysis for the reference check, the previous AR-VAD-based dealiasing method is improved to an AR-Var-based dealiasing method adaptively for radar radial velocities scanned wit

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27

Chen, Shengbo, Dashen Sun, and Huaikou Miao. "The Influence of Alias and References Escape on Java Program Analysis." International Journal of Networked and Distributed Computing 3, no. 1 (2015): 11. http://dx.doi.org/10.2991/ijndc.2015.3.1.2.

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28

Martins, Saulo S., Jandyr M. Travassos, and Mauricio D. Sacchi. "Interpolating GPR data using anti-alias singular spectrum analysis (SSA) method." Near Surface Geophysics 15, no. 5 (2017): 447–55. http://dx.doi.org/10.3997/nsg.155001.

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29

Whaley, John, and Monica S. Lam. "Cloning-based context-sensitive pointer alias analysis using binary decision diagrams." ACM SIGPLAN Notices 39, no. 6 (2004): 131–44. http://dx.doi.org/10.1145/996893.996859.

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30

Smith, J. Cole, and Sheldon H. Jacobson. "An Analysis of the Alias Method for Discrete Random-Variate Generation." INFORMS Journal on Computing 17, no. 3 (2005): 321–27. http://dx.doi.org/10.1287/ijoc.1030.0063.

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31

Zhang, Qirun, Michael R. Lyu, Hao Yuan, and Zhendong Su. "Fast algorithms for Dyck-CFL-reachability with applications to alias analysis." ACM SIGPLAN Notices 48, no. 6 (2013): 435–46. http://dx.doi.org/10.1145/2499370.2462159.

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32

Shen, Qiang, and Tossapon Boongoen. "Fuzzy Orders-of-Magnitude-Based Link Analysis for Qualitative Alias Detection." IEEE Transactions on Knowledge and Data Engineering 24, no. 4 (2012): 649–64. http://dx.doi.org/10.1109/tkde.2010.255.

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33

Kang, Yoohoon, Chanjin Park, and Chisu Wu. "Reverse-engineering 1-n associations from Java bytecode using alias analysis." Information and Software Technology 49, no. 2 (2007): 81–98. http://dx.doi.org/10.1016/j.infsof.2006.02.004.

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34

Fang, Xianhong, Zhaoqing Zhang, and Ruliang Qiao. "Interprocedural constant range propagation and alias analysis by multiple version method." Journal of Computer Science and Technology 10, no. 5 (1995): 403–16. http://dx.doi.org/10.1007/bf02948336.

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35

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 (1996): 99–130. http://dx.doi.org/10.1007/s002360050037.

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36

QIAN, Ju, Bao-Wen XU, and Yu-Ming ZHOU. "Interstatement Must Alias and Its Application in Dependence Analysis of Java Programs." Chinese Journal of Computers 31, no. 3 (2009): 419–30. http://dx.doi.org/10.3724/sp.j.1016.2008.00419.

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37

Woo, Jongwook, Jean-Luc Gaudiot, and Andrew L. Wendelborn. "Alias Analysis in Java with Reference-Set Representation for High-Performance Computing." International Journal of Parallel Programming 32, no. 1 (2004): 39–76. http://dx.doi.org/10.1023/b:ijpp.0000015564.82048.f3.

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38

Burke, Michael, and Jong-Deok Choi. "Precise and efficient integration of interprocedural alias information into data-flow analysis." ACM Letters on Programming Languages and Systems 1, no. 1 (1992): 14–21. http://dx.doi.org/10.1145/130616.130618.

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39

Ahrens, J. H., and U. Dieter. "An alias method for sampling from the normal distribution." Computing 42, no. 2-3 (1989): 159–70. http://dx.doi.org/10.1007/bf02239745.

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40

Lawson, John. "Regression analysis of experiments with complex confounding patterns guided by the alias matrix." Computational Statistics & Data Analysis 39, no. 2 (2002): 227–41. http://dx.doi.org/10.1016/s0167-9473(01)00056-1.

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41

Miyagi, S., and H. Sakai. "Convergence Analysis of Alias-Free Subband Adaptive Filters Based on aFrequency Domain Technique." IEEE Transactions on Signal Processing 52, no. 1 (2004): 79–89. http://dx.doi.org/10.1109/tsp.2003.820076.

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42

Pavlu, Viktor, Markus Schordan, and Andreas Krall. "Computation of alias sets from shape graphs for comparison of shape analysis precision." IET Software 8, no. 3 (2014): 120–33. http://dx.doi.org/10.1049/iet-sen.2012.0049.

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43

Jiang, Yuan, and Qin Xu. "Adaptive Dealiasing for Doppler Velocities Scanned from Hurricanes and Typhoons." Journal of Atmospheric and Oceanic Technology 33, no. 9 (2016): 1931–47. http://dx.doi.org/10.1175/jtech-d-15-0146.1.

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AbstractBy fitting a parametric vortex model directly to aliased radar radial velocities scanned from a hurricane, the maximum tangential velocity and its radial distance from the hurricane vortex center can be estimated by the recently developed alias-robust vortex analysis. This vortex analysis can be refined to produce a suitable reference radial velocity field on each tilt of a radar scan for the reference check in the first main step of dealiasing. This paper presents the techniques developed for the refinements and shows how and to what extent the refined vortex analysis can improve the

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44

Germane, Kimball, and Jay McCarthy. "Newly-single and loving it: improving higher-order must-alias analysis with heap fragments." Proceedings of the ACM on Programming Languages 5, ICFP (2021): 1–28. http://dx.doi.org/10.1145/3473601.

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Theories of higher-order must-alias analysis, often under the guise of environment analysis, provide deep behavioral insight. But these theories---in particular those that are most insightful otherwise---can reason about recursion only in limited cases. This weakness is not inherent to the theories but to the frameworks in which they're defined: machine models which thread the heap through evaluation. Since these frameworks allocate each abstract resource in the heap, the constituent theories of environment analysis conflate co-live resources identified in the abstract, such as recursively-cre

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45

Xu, Qin, and Kang Nai. "Mesocyclone-Targeted Doppler Velocity Dealiasing." Journal of Atmospheric and Oceanic Technology 34, no. 4 (2017): 841–53. http://dx.doi.org/10.1175/jtech-d-16-0170.1.

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AbstractThe alias-robust variational (AR-Var) analysis developed originally for dealiasing raw velocities scanned from winter ice storms by operational WSR-88D radars was recently extended for dealiasing raw velocities scanned from all storms to increase the dealiased data coverage. The extended AR-Var (eAR-Var)-based dealiasing can detect tornadic mesocyclones and estimate their vortex center locations as by-products, but its dealiased data often leave rejected data holes in the critical vortex core and vicinity areas of detected mesocyclones. To solve this problem, a mesocyclone-targeted dea

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46

BERGER, MARTIN, KOHEI HONDA, and NOBUKO YOSHIDA. "A logical analysis of aliasing in imperative higher-order functions." Journal of Functional Programming 17, no. 4-5 (2007): 473–546. http://dx.doi.org/10.1017/s0956796807006417.

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AbstractWe present a compositional programme logic for call-by-value imperative higher-order functions with general forms of aliasing, which can arise from the use of reference names as function parameters, return values, content of references and parts of data structures. The programme logic extends our earlier logic for alias-free imperative higher-order functions with new operators which serve as building blocks for clean structural reasoning about programms and data structures in the presence of aliasing. This has been an open issue since the pioneering work by Cartwright–Oppen and Morris

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47

Song, Chongmin, and John P. Wolf. "The scaled boundary finite element method?alias consistent infinitesimal finite element cell method?for diffusion." International Journal for Numerical Methods in Engineering 45, no. 10 (1999): 1403–31. http://dx.doi.org/10.1002/(sici)1097-0207(19990810)45:10<1403::aid-nme636>3.0.co;2-e.

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48

KENGNE, E., R. VAILLANCOURT, and B. A. MALOMED. "MODULATIONAL INSTABILITY AND EXACT SOLITON AND PERIODIC SOLUTIONS FOR TWO WEAKLY COUPLED EFFECTIVELY 1D CONDENSATES TRAPPED IN A DOUBLE-WELL POTENTIAL." International Journal of Modern Physics B 24, no. 14 (2010): 2211–27. http://dx.doi.org/10.1142/s021797921005541x.

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The modulational instability of the coupled Gross–Pitaevskii equation (alias nonlinear Schrödinger equation), which describes two Bose–Einstein condensates trapped in an asymmetric double-well potential, is investigated. The nonlinear dispersion relation that relates the frequency and wave number of the modulating perturbations is found and its analysis shows several possibilities for the modulational stability region. Exact soliton and periodic solutions are constructed via elliptic ordinary differential equations.

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49

Usevitch, B. E., and C. L. Betancourt. "Fixed-point error analysis of two-channel perfect reconstruction filter banks with perfect alias cancellation." IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing 46, no. 11 (1999): 1437–40. http://dx.doi.org/10.1109/82.803484.

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50

Hill, Michael D., Renee H. Martin, Yuko Y. Palesch, et al. "Albumin Administration in Acute Ischemic Stroke: Safety Analysis of the ALIAS Part 2 Multicenter Trial." PLOS ONE 10, no. 9 (2015): e0131390. http://dx.doi.org/10.1371/journal.pone.0131390.

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