Clustered serialization with fuel

Dias, Martín; Peck, Mariano Martinez; Ducasse, Sté́phane; Arévalo, Gabriela

doi:10.1145/2166929.2166930

Cited by 9 publications

(10 citation statements)

References 18 publications

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“…Control Serialized Objects. Fuel [DPDA11] allows the serialization of all objects reachable from a certain starting object, exceptions and stack traces comprised. While this is a desirable property for a serializer, this may become problematic when employing it for an out-of-place debugger.…”

Section: Discussionmentioning

confidence: 99%

“…The IDRA Monitor controls the target application and suspends its execution when it finds a breakpoint. Every time a breakpoint is hit, the IDRA Monitor serializes the stack trace and all objects reachable from it using the Fuel serializer [DPDA11] and sends it to the IDRA Manager. Fuel will serialize the contexts of the call stack and all the objects referenced from each context.…”

Section: Out-of-place Debugging In Pharomentioning

confidence: 99%

See 1 more Smart Citation

Debugging Cyber-Physical Systems with Pharo

Marra

Boix

Costiou

et al. 2017

Proceedings of the 12th Edition of the International Workshop on Smalltalk Technologies

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Cyber-Physical Systems (CPS) integrate sensors and actuators to collect data and control entities in the physical world. Debugging CPS systems is hard due to the time-sensitive nature of a distributed applications combined with the lack of control on the surrounding physical environment. This makes bugs in CPS systems hard to reproduce and thus to fix. In this context, on-line debugging techniques are helpful because the debugger is connected to the device when an exception or crash occurs. This paper reports on our experiences on applying two different on-line debugging techniques for a CPS system: remote debugging using the Pharo remote debugger and our IDRA debugger. In contrast to traditional remote debugging, IDRA allows to on-line debug an application locally in another client machine by reproducing the runtime context where the bug manifested. Our qualitative evaluation shows that IDRA provides almost the same interaction capabilities than Pharo's remote debugger and is less intrusive when performing hot-modifications. Our benchmarks also show that IDRA is significantly faster than the Pharo remote debugger, although it increases the amount of data transferred over the network.

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Section: Discussionmentioning

confidence: 99%

Section: Out-of-place Debugging In Pharomentioning

confidence: 99%

Debugging Cyber-Physical Systems with Pharo

Marra

Boix

Costiou

et al. 2017

Proceedings of the 12th Edition of the International Workshop on Smalltalk Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…Marea is fully implemented 14 [DMPDA11]). In this section, we explain Marea's design and its requirements from the programming language.…”

Section: Methodsmentioning

confidence: 99%

Marea: An Efficient Application-Level Object Graph Swapper.

Peck¹,

Bouraqadi²,

Denker³

et al. 2013

JOT

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During the execution of object-oriented applications, several millions of objects are created, used and then collected if they are not referenced. Problems appear when objects are unused but cannot be garbage-collected because they are still referenced from other objects. This is an issue because those objects waste primary memory and applications use more primary memory than they actually need. We claim that relying on the operating system's (OS) virtual memory is not always enough since it cannot take into account the domain and structure of applications. At the same time, applications have no easy way to parametrize nor cooperate with memory management. In this paper, we present Marea, an efficient application-level object graph swapper for object-oriented programming languages. Its main goal is to offer the programmer a novel solution to handle application-level memory. Developers can instruct our system to release primary memory by swapping out unused yet referenced objects to secondary memory. Our approach has been qualitatively and quantitatively validated. Our experiments and benchmarks on real-world applications show that Marea can reduce the memory footprint between 23% and 36%.

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“…Since stack reifications appear to the language as normal heap allocated objects, they can be serialized and transferred like any other object. To serialize, we use Fuel [6], a standard serialization library in Pharo. For network communication between different threads, we use Zinc 5 , the same HTTP framework we presented as use case.…”

Section: Serializing Call-stacksmentioning

confidence: 99%

Framework-aware debugging with stack tailoring

Marra

Polito

Boix

2020

Proceedings of the 16th ACM SIGPLAN International Symposium on Dynamic Languages

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Debugging applications that execute within a framework is not always easy: the call-stack offered to developers is often a mix-up of stack frames that belong to different frameworks, introducing an unnecessary noise that prevents developers from focusing on the debugging task. Moreover, relevant application code is not always available in the call-stack because it may have already returned, or is available in another thread. In such cases, manually gathering all relevant information from these different sources is not only cumbersome but also costly.In this paper we introduce Sarto, a call-stack instrumentation layer that allows developers to tailor the stack to make debugging framework-aware. The goal is to improve the quality and amount information present in the call-stack to reduce debugging time without impacting the execution time. Sarto proposes a set of six stack operations that combined hide irrelevant information, introduce missing information, and relate dispersed debugging sources before this is fed to the debugger.We validate Sarto by applying it to four application cases using inherently different frameworks: unit testing, web server, remote promises and big data processing. We showcase our experiences in using Sarto in the different frameworks, and perform some performance benchmarks to demonstrate that Sarto does not generate noticeable overhead when instrumenting a call-stack. We also show that our solution reduces by half the amount of data stored to debug similar exceptions happening in a parallel setup.CCS Concepts: • Software and its engineering → Application specific development environments; Integrated and visual development environments; Error handling and recovery; Software testing and debugging.

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Clustered serialization with fuel

Cited by 9 publications

References 18 publications

Debugging Cyber-Physical Systems with Pharo

Debugging Cyber-Physical Systems with Pharo

Marea: An Efficient Application-Level Object Graph Swapper.

Framework-aware debugging with stack tailoring

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