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Dive into the research topics where William J. Aldrich is active.

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Featured researches published by William J. Aldrich.


AIAA Modeling and Simulation Technologies Conference and Exhibit | 2002

Using Model Coverage Analysis to Improve the Controls Development Process

William J. Aldrich

Graphical simulation tools improve the effectiveness and efficiency of embedded controls development by providing an abstract view of a component or system in a visual paradigm. These modeling tools have unambiguous semantics and can execute designs. Coverage analysis can indicate the completeness and consistency of a set of requirements. Recent advances in code synthesis allow very efficient code to be produced directly from the graphical models. When generated code is used without modification model-based coverage analysis is more effective than the same analysis performed on generated code. Coverage analysis within a modeling tool should be consistent with the executable semantics of the tool and should be presented in a form that is easily associated with the graphical diagrams.


Archive | 2013

Mapping between code coverage and model coverage for a design

William J. Aldrich; Mirko Conrad


Archive | 2010

Test postcondition items for automated analysis and test generation

William J. Aldrich


Archive | 2005

Visual representation of model execution results contributing to a failure condition in a model

William J. Aldrich


Archive | 2008

Verification and validation system for a graphical model

William J. Aldrich; Grégoire Hamon


Archive | 2001

Linked code generation report

Kai Tuschner; William J. Aldrich


Archive | 2011

Partitioning block diagrams into executable contextual models

William J. Aldrich; Ebrahim Mehran Mestchian; Denizhan N. Alparslan


Archive | 2011

Reversed links from graphical diagram representation

William J. Aldrich


Archive | 2011

Determining model components suitable for verification analysis

William J. Aldrich; Ebrahim Mehran Mestchian; Denizhan N. Alparslan


Archive | 2013

System and method for identifying and reducing model complexities affecting model verification

William J. Aldrich

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