A probe effect in concurrent programs

Gait, Jason

doi:10.1002/spe.4380160304

Cited by 149 publications

(41 citation statements)

References 6 publications

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“…Indeed, tracing solutions need to be highly optimized as they should only minimally impact the monitored system, to avoid the undesired "probe effect" [9].…”

Section: Related Workmentioning

confidence: 99%

Low-level trace correlation on heterogeneous embedded systems

Bertauld

Dagenais

2017

J Embedded Systems

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Tracing is a common method used to debug, analyze, and monitor various systems. Even though standard tools and tracing methodologies exist for standard and distributed environments, it is not the case for heterogeneous embedded systems. This paper proposes to fill this gap and discusses how efficient tracing can be achieved without having common system tools, such as the Linux Trace Toolkit (LTTng), at hand on every core. We propose a generic solution to trace embedded heterogeneous systems and overcome the challenges brought by their peculiar architectures (little available memory, bare-metal CPUs, or exotic components for instance). The solution described in this paper focuses on a generic way of correlating traces among different kinds of processors through traces synchronization, to analyze the global state of the system as a whole. The proposed solution was first tested on the Adapteva Parallella board. It was then improved and thoroughly validated on TI's Keystone 2 System-on-Chip (SoC).

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“…Indeed, tracing solutions need to be highly optimized as they should only minimally impact the monitored system, to avoid the undesired "probe effect" [9].…”

Section: Related Workmentioning

confidence: 99%

Low-level trace correlation on heterogeneous embedded systems

Bertauld

Dagenais

2017

J Embedded Systems

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“…However, any form of observation is also an interaction -the act of testing can also affect what is being tested. In [30], Jason Gait defined the probe effect as "a characteristic behaviour of the execution trace of an incorrectly synchronized concurrent program when extraneous delays are introduced". In some situations, the presence of the debugger or the act of observation can affect some timing-related bugs in such a way that the bug disappears or the threads switch their execution order.…”

Section: Software Testing and Debuggingmentioning

confidence: 99%

Sampling-based program execution monitoring

Fischmeister

2010

SIGPLAN Not.

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For its high overall cost during product development, program debugging is an important aspect of system development. Debugging is a hard and complex activity, especially in time-sensitive systems which have limited resources and demanding timing constraints.System tracing is a frequently used technique for debugging embedded systems. A specific use of system tracing is to monitor and debug control-flow problems in programs. However, it is difficult to implement because of the potentially high overhead it might introduce to the system and the changes which can occur to the system behaviour due to tracing.To solve the above problems, in this work, we present a sampling-based approach to program execution monitoring which specifically helps developers trace the program execution in time-sensitive systems such as real-time applications. We build the system model and propose three theorems which determine the sampling period or the optimal in different scenarios. We also design seven heuristics and an instrumentation framework to extend the sampling period which can reduce the monitoring overhead and achieve an optimal tradeoff between accuracy and overhead introduced by instrumentation. Using this monitoring framework, we can use the information extracted through sampling to reconstruct the system state and execution paths to locate the deviation. Based on the statistically significant data, we also model the trend of the sampling period with the instrumentation steps. Based on the modelling results, we devise a scheme for predicting the number of markers we need to reach a certain sampling period. Last, we build a tool chain to instrument and monitoring the software system and further prove the soundness of our approach.

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“…This means, if we assume communication latencies in the interval [3,6), that task C can receive data from task instance E 2 or E 3 . In order to differentiate between these scenarios we should therefore substitute the global ordering (q1,p1) with the set (q1:C(E 2 ), p1) and (q1:C(E 3 ), p1).…”

Section: Example 3-2mentioning

confidence: 99%

“…However, trying to directly apply test techniques for sequential programs on distributed real-time systems is bound to lead to non-determinism and non-reproducibility, because control is only forced on the inputs, disregarding the significance of order and timing of the executing and communicating tasks. Any intrusive observation of a distributed real-time system will, in addition, incur a temporal probe-effect [6][18] that subsequently will affect the temporal and functional behavior of the system.…”

Section: Introductionmentioning

confidence: 99%