A comparison of system monitoring methods, passive network monitoring and kernel instrumentation
ACM SIGOPS Operating Systems Review
An Embedded Software Primer
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
A Tool for Analyzing and Fine Tuning the Real-Time Properties of an Embedded System
IEEE Transactions on Software Engineering
Gprof: A call graph execution profiler
SIGPLAN '82 Proceedings of the 1982 SIGPLAN symposium on Compiler construction
Software Testing, Verification & Reliability
Using Dynamic Kernel Instrumentation for Kernel and Application Tuning
International Journal of High Performance Computing Applications
Testing in resource constrained execution environments
Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering
Low overhead program monitoring and profiling
PASTE '05 Proceedings of the 6th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
Information and Software Technology
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Despite advances in software testing technologies, there are still limitations in directly applying them to embedded software. Since the operational environment of embedded software has severe resource constraints, it is necessary to develop a lightweight testing method that has little impact on the operational environment of embedded software. We propose an agent-based performance analysis method to hack kernel performance counters that manage the system's execution information. The proposed method enables us to collect data required for analyzing performance bottlenecks and identify the causes and locations of bottlenecks with little impact on the test target system's operational environment. We introduce a test automation tool called Analytic Master of System v2.0 that we developed by employing our proposed method. Presently, Analytic Master of System v2.0 is being utilized as a standard tool for performance testing of embedded systems in the automotive industry. In addition, we suggest a guideline for performance analysis and improvement by introducing an industrial field study among our best practices, which analyze the relationship between the memory fault processing of the operating system and the application processing speed.