scholarly journals Practical SMT-based type error localization

2015 ◽  
Author(s):  
Zvonimir Pavlinovic ◽  
Tim King ◽  
Thomas Wies
Keyword(s):  
Error Localization

ERROR LOCALIZATION DIAGNOSTIC MODEL OPTIMIZATION IN DIGITAL STATE MACHINES NETWORKS

2019 ◽  
Author(s):  
Irina Bystrova ◽  
E. Danil'chuk ◽  
Boris Podkopaev
Keyword(s):  
Single Component ◽  
Diagnostic Model ◽  
State Machines ◽  
Model Optimization ◽  
Error Localization ◽  
Diagnostic Models

The problem of constructing a diagnostic model for a network S consisting of a number of digital automata is considered, provided that the diagnostic models of all network components are known. It is assumed that these models are given by systems of logical equations, and the errors to be detected are localized in any but a single component of the network.

Automated Design Error Localization in RTL Designs

2014 ◽  
Vol 31 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Maksim Jenihhin ◽  
Anton Tsepurov ◽  
Valentin Tihhomirov ◽  
Jaan Raik ◽  
Hanno Hantson ◽  
...  
Keyword(s):  
Automated Design ◽  
Design Error ◽  
Error Localization

Reliable Mode Shape Expansion Method for Error Localisation and Model Updating

1997 ◽  
Author(s):  
Philippe Collignon ◽  
Jean-Claude Golinval
Keyword(s):  
Cantilever Beam ◽  
Mode Shape ◽  
Constitutive Equations ◽  
Structural Model ◽  
Model Updating ◽  
Failure Detection ◽  
Expansion Method ◽  
Relative Performance ◽  
Mode Shapes ◽  
Error Localization

Abstract Failure detection and model updating using structural model are based on the comparison of an appropriate indicator of the discrepancy between experimental and analytical results. The reliability of the expansion of measured mode shapes is very important for the process of error localization and model updating. Two mode shape expansion techniques are examined in this paper : the well known dynamic expansion (DE) method and a method based on the minimisation of errors on constitutive equations (MECE). A new expansion method based on some improvements of the previous techniques is proposed to obtain results that are more reliable for error localisation and for model updating. The relative performance of the different expansion methods is demonstrated on the example of a cantilever beam.

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