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  1. Proceedings of the 2002 ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (PASTE '02)
  2. Selective path profiling
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Monitoring deployed software using software tomography
STEP: a framework for the efficient encoding of general trace data
Using the observer design pattern for implementation of data flow analyses
Longitudinal program analysis
Recompilation for debugging support in a JIT-compiler
Selective path profiling
Flow equations as a generic programming tool for manipulation of attributed graphs
Analysis issues for cyclone
Instruction-level reverse execution for debugging
Combining static and dynamic data in code visualization
The code of many colors: relating threads to code and shared state
How to write system-specific, static checkers in metal

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Selective path profiling

Content Provider ACM Digital Library
Author Harrold, Mary Jean Apiwattanapong, Taweesup
Abstract Recording dynamic information for only a subset of program entities can reduce monitoring overhead and can facilitate efficient monitoring of deployed software. Program entities, such as statements, can be monitored using probes that track the execution of those entities. Monitoring more complicated entities, such as paths or definition-use associations, requires more sophisticated techniques that track not only the execution of the desired entities but also the execution of other entities with which they interact. This paper presents an approach for monitoring subsets of one such program entity---acyclic paths in procedures. Our selective path profiling algorithm computes values for probes that guarantee that the sum of the assigned value along each acyclic path (path sum) in the subset is unique; acyclic paths not in the subset may or may not have unique path sums. The paper also presents the results of studies that compare the number of probes required for subsets of various sizes with the number of probes required for profiling all paths, computed using Ball and Larus' path profiling algorithm. Our results indicate that the algorithm performs well on many procedures by requiring only a small percentage of probes for monitoring the subset.
Starting Page 35
Ending Page 42
Page Count 8
File Format PDF
ISBN 1581134797
DOI 10.1145/586094.586104
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2002-11-18
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Dynamic analysis Path profiling Static analysis
Content Type Text
Resource Type Article
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