Judith B. Peachey

dblp:89/2841 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 1985
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Performance modeling and evaluation · 50% Memory systems · 50%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Performance modeling and evaluation › workload characterization
program behavior analysis
0.011985
Some Empirical Observations on Program Behavior with Applications to Program Restructuring · IEEE Trans. Software Eng. 1985
Memory systems › memory management › virtual memory
program restructuring
0.011985
Some Empirical Observations on Program Behavior with Applications to Program Restructuring · IEEE Trans. Software Eng. 1985
Memory systems › memory management
virtual memory
0.011985
Some Empirical Observations on Program Behavior with Applications to Program Restructuring · IEEE Trans. Software Eng. 1985
Performance modeling and evaluation
workload characterization
0.011985
Some Empirical Observations on Program Behavior with Applications to Program Restructuring · IEEE Trans. Software Eng. 1985

Methods — techniques the papers use, named apart from their topics

clustering · 0.0bradford-zipf analysis · 0.0
YearPublicationVenuePosition
1985 Some Empirical Observations on Program Behavior with Applications to Program Restructuring
abstract
The dynamic behavior of executing programs is a significant factor in the performance of virtual memory computer systems. Program restructuring attempts to improve the behavior of programs by reorganizing their object code to account for the characteristics of the virtual memory environment. A significant component of the restructuring process involves a restructuring graph. An analysis of restructuring graphs of typical programs found edge weights to be distributed in a Bradford–Zipf fashion, implying that a large fraction of total edge weight is concentrated in relatively few edges. This empirical observation can be used to improve the clustering phase of program restructuring, by limiting consideration to edges of large weight. We consider the effect of this improved clustering in the restructuring process by examining various means of restructuring some typical programs. In our experiments, 95 percent of the total edge value is typically accounted for by 50–60 percent of the edges. For naive clustering algorithms, clustering time is therefore typically halved; for more sophisticated methods, more substantial savings result. Finally, clustering with 95 percent of total edge value typically results in only a small decay in performance measures such as number of page faults and average working set size.
Judith B. Peachey, Richard B. Bunt, Charles J. Colbourn
IEEE Trans. Software Eng.1