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Moshe Klausner

dblp:55/6941 · DBLP profile ↗
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3ranked-venue papers
0as first author
0since 2021 · last 2009
—ORCID · none

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

Systems, architecture and hardware · 2Software engineering, systems software and programming languages · 2

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.

Software engineering, system software, and programming languages
1 paper
Software testing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing › test coverage
code coverage
0.112009
Advanced code coverage analysis using substring holes · ISSTA 2009
Software testing
test coverage
0.112009
Advanced code coverage analysis using substring holes · ISSTA 2009

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

substring holes · 0.1
YearPublicationVenuePosition
2009 Advanced code coverage analysis using substring holes
abstract
Code coverage is a common aid in the testing process. It is generally used for marking the source code segments that were executed and, more importantly, those that were not executed.
Yoram Adler, Eitan Farchi, Moshe Klausner, Dan Pelleg, Orna Raz, Moran Shochat, Shmuel Ur, Aviad Zlotnick
ISSTA3
2008 Aggressive Function Inlining: Preventing Loop Blockings in the Instruction Cache
Yosi Ben-Asher, Omer Boehm, Daniel Citron, Gadi Haber, Moshe Klausner, Roy Levin, Yousef Shajrawi
HiPEAC5
2003 Optimization Opportunities Created by Global Data Reordering
abstract
Memory access has proven to be one of the bottlenecks in modern architectures. Improving memory locality and eliminating the amount of memory access can help release this bottleneck. We present a method for link-time profile-based optimization by reordering the global data of the program and modifying its code accordingly. The proposed optimization reorders the entire global data of the program, according to a representative execution rate of each instruction (or basic block) in the code. The data reordering is done in a way that enables the replacement of frequently-executed Load instructions, which reference the global data, with fast Add Immediate instructions. In addition, it tries to improve the global data locality and to reduce the total size of the global data area. The optimization was implemented into FDPR (Feedback Directed Program Restructuring), a post-link optimizer, which is part of the IBM AIX operating system for the IBM pSeries servers. Our results on SPECint2000 show a significant improvement of up to 11% (average 3%) in execution time, along with up to 97.9% (average 83%) reduction in memory references to the global variables via the global data access mechanism of the program.
Gadi Haber, Moshe Klausner, Vadim Eisenberg, Bilha Mendelson, Maxim Gurevich
CGO2