Self-Service Linux: Determining Problems and Finding Solutions
Self-Service Linux: Determining Problems and Finding Solutions
Linux Debugging and Performance Tuning: Tips and Techniques
Linux Debugging and Performance Tuning: Tips and Techniques
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
Valgrind: a framework for heavyweight dynamic binary instrumentation
Proceedings of the 2007 ACM SIGPLAN conference on Programming language design and implementation
JIT instrumentation: a novel approach to dynamically instrument operating systems
Proceedings of the 2nd ACM SIGOPS/EuroSys European Conference on Computer Systems 2007
Tolerating hardware device failures in software
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Debugging in the (very) large: ten years of implementation and experience
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Improving application security with data flow assertions
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
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As the use of embedded Linux kernel increases in a variety of consumer electronics such as Smart phones and Internet TVs, the significance of effective kernel profiling and debugging tools also increases. In this paper, we propose a novel integrated kernel analysis tool. It supports two features, right time and right place feature, thus we call it as RTRP (Right Time Right Place) tool. The right time feature is supported by monitoring system performance on-line and by issuing a debugging trigger automatically at the time when the target system shows performance anomalies or misbehaviors. It is a kind of semantic-aware debugging based on the context of Linux kernel. In addition, the tool supports the right place feature by providing proper system information including the stack frame and call graphs that causes the problems, allowing developers to focus on solving the problems without being deviated by irrelevant information. Experimental results, conducted on a real embedded system equipped with a live image compression facility, have shown that the tool can notify appropriate information to identify the location of a device driver that causes overrun problems.