Parameterized Memory Models
Parameterized Memory Models is a computational framework in memory modeling that specifies memory processes through adjustable parameters, distinguishing itself by enabling quantitative predictions of memory behavior across varying experimental conditions via systematic manipulation of its formal parameters.
24
Publications
1.8K
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61
Authors
39
Institutions
Publications per year
2017–2026
4
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Model checking for weakly consistent libraries
Michalis Kokologiannakis, Azalea Raad, Viktor Vafeiadis · 2019 · 83 citations · Full text
Parametric prediction of heap memory requirements
Vı́ctor Braberman, F.J. Fernandez, Diego Garbervetsky et al. · 2008 · 72 citations
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Leiden University
Leiden, The Netherlands
2 h-index
2 publications
103 citations

Lund University
Lund, Sweden
2 h-index
3 publications
66 citations
Universidad de Buenos Aires
Buenos Aires, Argentina
2 h-index
3 publications
118 citations
Verimag
Gières, France
2 h-index
2 publications
110 citations
KU Leuven
Leuven, Belgium
2 h-index
2 publications
56 citations
University of Utah
Salt Lake City, United States
1 h-index
3 publications
99 citations
Bielefeld University
Bielefeld, Germany
1 h-index
2 publications
28 citations
Carnegie Mellon University
Pittsburgh, United States
1 h-index
2 publications
1.9K citations
1–8 of 39
2 publications · 73 citations
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JOT · 1 publications · 38 citations
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1 publications · 958 citations
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Conference · 1 publications · 15 citations
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1 publications · 12 citations
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