Computing quantitative characteristics of finite-state real-time systems

Campos, Antonìo; Clarke,; Marrero,; Minea,; Hiraishi,

doi:10.1109/real.1994.342709

Cited by 65 publications

(42 citation statements)

References 5 publications

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“…As before, the algorithm is implemented using BDDs, however, a backward search is required in this case. Both algorithms are proven correct in [10].…”

Section: Quantitative Analysismentioning

confidence: 95%

“…These verifiers assume that timing constraints are given explicitly in some notation like temporal logic and determine if the system satisfies the constraint. In [10] we have described how to verify timing properties using algorithms that explicitly compute timing information as opposed to simply checking a formula. This section briefly describes that approach, which is later used in this work.…”

Section: Quantitative Analysismentioning

confidence: 99%

“…For this reason designers of real-time systems often significantly reduce asynchronism in their systems to ensure predictability. In fact, several real-time systems we have analyzed are even more synchronous than traditional circuits, and have been successfully verified using techniques such as the one proposed [10,9,8].…”

Section: Introductionmentioning

confidence: 99%

“…In [10] it has been proposed how quantitative symbolic algorithms can be used to analyze the model of a system. The technique suggested there computes minimum and maximum delays between the occurrence of two events, as well as the number of times a specified condition occurs in such an interval.…”

Section: Introductionmentioning

confidence: 99%

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Selective quantitative analysis and interval model checking: Verifying different facets of a system

Campos

Grumberg

1996

Computer Aided Verification

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In this work we propose a verification methodology consisting of selective quantitative analysis and interval model checking. Our methods can aid not only in determining if a system works correctly, but also in understanding how well the system works.The selective quantitative algorithms compute minimum and maximum delays over a selected subset of system executions. We use a formula of the linear-time temporal logic LTL in order to select either infinite paths or finite intervals over which the computation is performed. We therefore define two semantics for LTL -over infinite paths and over finite intervals. We show how tableaux for LTL formulas can be used for selecting either paths or intervals and can also be used for model checking formulas interpreted over paths or intervals.We have implemented a tool based on our techniques. To demonstrate the usefulness of our methods we verified a complex distributed real-time system. Several features of this example make it an interesting target for our techniques. It is a system of realistic complexity, its components are existing systems and protocols executing a mixture of multimedia, traditional real-time and non-real time tasks. Also, the distributed nature of the system makes the interaction among its various components much richer. This also makes its analysis more difficult.Out tool were able to analyze the system and verify that the deadlines are met by the design. Moreover, we have been able to identify inefficiencies that caused the response time to increase significantly (about 50%). After changing the design we not only verified that the response time was lower, but were also able to determine the causes for the poor performance of the original model using interval model checking.

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“…As before, the algorithm is implemented using BDDs, however, a backward search is required in this case. Both algorithms are proven correct in [10].…”

Section: Quantitative Analysismentioning

confidence: 95%

Section: Quantitative Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Campos

Grumberg

1996

Computer Aided Verification

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“…Similarly, it is common to observe complex real-time behaviour in such systems. Model checking of discrete-time systems against properties of timed temporal logics, which can refer to the time elapsed along system behaviours, has been studied extensively in, for example, [11,6,16].…”

Section: Introductionmentioning

confidence: 99%

Model Checking Durational Probabilistic Systems

Laroussinie

Sproston

2005

Foundations of Software Science and Computational Structures

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Abstract. We consider model-checking algorithms for durational probabilistic systems, which are systems exhibiting nondeterministic, probabilistic and discrete-timed behaviour. We present two semantics for durational probabilistic systems, and show how formulae of the probabilistic and timed temporal logic PTCTL can be verified on such systems. We also address complexity issues, in particular identifying the cases in which model checking durational probabilistic systems is harder than verifying non-probabilistic durational systems.

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Real-Time and Fault-Tolerant Systems

Liu

Joseph²

2006

Refinement Techniques in Software Engineering

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Computing quantitative characteristics of finite-state real-time systems

Cited by 65 publications

References 5 publications

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Selective quantitative analysis and interval model checking: Verifying different facets of a system

Model Checking Durational Probabilistic Systems

Real-Time and Fault-Tolerant Systems

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