Self-stabilization Preserving Compiler

Haviv, Yinnon; Sagiv, Mooly

doi:10.1007/11577327_6

Cited by 11 publications

(11 citation statements)

References 16 publications

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“…We have implemented [Dolev et al 2008] the compiler in order to validate our design and provide a workbench for writing self-stabilizing algorithms. The implementation used Java as a programming language and JavaCC as a parser generator.…”

Section: Discussionmentioning

confidence: 99%

“…The system allows the simulation of atomic, regular and safe registers and encourages read and write operations to overlap by delaying the scheduling of processors that are currently in IO actions. The plug-in, its manuals and sources can be found in Dolev et al [2008].…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, after the stabilization, the "token" (the permission to enter the critical section) is passed in the ring from each processor to the next. The code that appears in this section is taken from the example that appears in Dolev et al [2008] and can be compiled by the implementation of the compiler. The code executed by the agents is described in Figures 17 and 18.…”

Section: A Example: Self-stabilizing Algorithm For Mutual Exclusion mentioning

confidence: 99%

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Self-stabilization preserving compiler

Haviv

Sagiv

2009

ACM Trans. Program. Lang. Syst.

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Self-stabilization is an elegant approach for designing fault tolerant systems. A system is considered self-stabilizing if, starting in any state, it converges to the desired behavior. Self-stabilizing algorithms were designed for solving fundamental distributed tasks, such as leader election, token circulation and communication network protocols. The algorithms were expressed using guarded commands or pseudo-code. The realization of these algorithms requires the existence of a (selfstabilizing) infrastructure such as a self-stabilizing microprocessor and a self-stabilizing operating system for their execution. Moreover, the high-level description of the algorithms needs to be converted into machine language of the microprocessor. In this article, we present our design for a self-stabilization preserving compiler. The compiler we designed and implemented transforms programs written in a language similar to the abstract state machine (ASM). The compiler preserves the stabilization property of the high level program.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: A Example: Self-stabilizing Algorithm For Mutual Exclusion mentioning

confidence: 99%

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Self-stabilization preserving compiler

Haviv

Sagiv

2009

ACM Trans. Program. Lang. Syst.

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“…Related Work Self-stabilization was initially developed as an approach to build distributed algorithms that were robust to failures [3]. Dolev et al [5], [6], [4] recently developed an approach that ensures that the underlying layers (processor, operating system, and compiler) preserve the self-stabilizing nature of an application. This earlier work does not check that the actual application is self-stabilizing.…”

Section: Robot Controllermentioning

confidence: 99%

“…4 A shortest common supersequence problem can be represented as our minimization problem by creating a unique path for each input sequence, encoding 0 with a normal node and 1 with a shared node. Thus finding an optimal solution to our problem is at least as difficult as the shortest common supersequence problem.…”

Section: E Inserting Local Variable Locationsmentioning

confidence: 99%

Sinfer: Inferring information flow lattices for checking self-stabilization

Eom

Demsky

2013

2013 IEEE 24th International Symposium on Software Reliability Engineering (ISSRE)

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Self-stabilizing programs are guaranteed to recover from state corruption caused by software bugs or other events and eventually reach the correct state. Many real-world applications including embedded controllers and multimedia applications can be designed to make key components self-stabilizing.Type systems and static analyses can automatically check whether a program is self stabilizing. The existing approach for checking self-stabilization requires developers to manually annotate code. We present an annotation inference algorithm that automatically derives an initial set of annotations and therefore lowers the effort to build self-stabilizing systems. Our experience with the algorithm indicates that it effectively inferred annotations for our benchmarks.

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Self-stabilization Preserving Compiler

Haviv

Sagiv

2005

Lecture Notes in Computer Science

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Self-stabilization Preserving Compiler

Cited by 11 publications

References 16 publications

Self-stabilization preserving compiler

Self-stabilization preserving compiler

Sinfer: Inferring information flow lattices for checking self-stabilization

Self-stabilization Preserving Compiler

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