Logic of Constraints: A Quantitative Performance and Functional Constraint Formalism

Chen, Xi; Hsieh, Harry; Balarin, Felice; Watanabe, Yosinori

doi:10.1109/tcad.2004.831575

Cited by 16 publications

(6 citation statements)

References 28 publications

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“…It is known that only a subset of LOC can be translated into equivalent LTL formulas and formally checked with Spin directly. (9) For the rest of the LOC formulas, the formal verification results may be inconclusive, i.e. the verification is only partial.…”

Section: Formal Verification Methodologymentioning

confidence: 99%

Verification Approach of Metropolis Design Framework for Embedded Systems

Chen

Hsieh

Balarin

2006

Int J Parallel Prog

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In this paper, we focus on the verification approach of Metropolis, an integrated design framework for heterogeneous embedded systems. The verification approach is based on the formal properties specified in Linear Temporal Logic (LTL) or Logic of Constraints (LOC). Designs may be refined due to synthesis or be abstracted for verification. An automatic abstraction propagation algorithm is used to simplify the design for specific properties. A user-defined starting point may also be used with automatic propagation. Two main verification techniques are implemented in Metropolis: the formal verification utilizing the model checker Spin and the simulation trace checking with automatic generated checkers. Translation algorithms from specification models to verification models, as well as algorithms of generated checkers are discussed. We use several case studies to demonstrate our approach for verification of system level designs at multiple levels of abstraction.

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Section: Formal Verification Methodologymentioning

confidence: 99%

Verification Approach of Metropolis Design Framework for Embedded Systems

Chen

Hsieh

Balarin

2006

Int J Parallel Prog

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“…The Logic of Constraints checker 17 allows the user to generate an executable checker from formulas written in a formal quantitative constraint language. An evaluation report is generated by running this executable on simulation traces.…”

Section: Related Workmentioning

confidence: 99%

Execution trace‐based model verification to analyze multicore and real‐time systems

Beamonte

Ezzati‐Jivan

Dagenais

2022

Concurrency and Computation

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As a key part of model‐driven development, modeling allows users to represent the application workflow or to automatically generate source code. This is convenient for developers, particularly to create or improve real‐time applications embedded in complex systems. Multicore systems are difficult to debug because the concurrently running processes can interfere with each other. In real‐time systems, timing constraints add to the complexity, invalidating results when a deadline is missed. Tracing is usually the most accurate and reliable tool to study the runtime behaviour of those applications. However, the interpretation of voluminous detailed execution traces requires a deep understanding of the operating system and application behaviour, and time to dig through the millions of trace events.In this paper, we present the use of model‐based constraints on top of user‐space and kernel traces to provide weighted analysis results. Our algorithms have been applied to multiple traces showing common problems for multi‐core real‐time systems. The experimental results show that our algorithms can quickly identify many different types of problems with a low runtime, even for traces with millions of events, thus helping to save time when analyzing thousands of trace events for complex systems.

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“…Chen et al [9] suggest to analyze simulation traces of systems, including hardware/software models, to check if functional and performance constraints expressed in Logic of Constraints (LoC) [24] are satisfied. A trace checker reports any constraint violation of a simulation trace.…”

Section: A Simulation Traces Analysismentioning

confidence: 99%