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140122 ||| eng |
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|a 9781461536062
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| 100 |
1 |
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|a Butler, Kenneth M.
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| 245 |
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|a Assessing Fault Model and Test Quality
|h Elektronische Ressource
|c by Kenneth M. Butler, M. Ray Mercer
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| 250 |
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|a 1st ed. 1992
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| 260 |
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|a New York, NY
|b Springer US
|c 1992, 1992
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| 300 |
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|a XIX, 132 p
|b online resource
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| 505 |
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|a 1. Introduction -- 1.1 Functional Test Generation Techniques -- 1.2 Representing Symmetric Functions with OBDDs -- 1.3 Controllability, Observability, and Detectability -- 1.4 Modeling ATPG and Measuring Test Quality -- 2. Fault Modeling -- 2.1 Fault Model Assumptions -- 2.2 Fault Model Classes -- 3. Ordered Binary Decision Diagrams -- 3.1 History of OBDDs -- 3.2 Properties of OBDDs -- 3.3 Shannon’s Expansion Theorem -- 4. Automatic Test Pattern Generation -- 4.1 ATPG Problem Specification -- 4.2 Conventional ATPG Algorithms -- 4.3 Boolean Functional Test Generation -- 5. Defect Level -- 5.1 Definition of Defect Level -- 5.2 Defect Level Simplifying Assumptions -- 5.3 Defect Level Models -- 6. Test Performance Evaluation -- 6.1 Theoretical Approaches -- 6.2 Fault Simulation Approaches -- 6.3 Test Application Approaches -- 6.4 Layout Driven Approaches -- 7. OBDDs for Symmetric Functions -- 7.1 Symmetric Functions -- 7.2 Circuit and Function Terminology --
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|a 11.7 Implications to Defect Level -- 12. Conclusions -- 13.Suggestions for Future Research -- 13.1 Extensions to OBDD Size Research -- 13.2 Extensions to Difference Propagation -- 13.3 Extensions to Test Quality Research -- 13.4 Using Ordered Partial Decision Diagrams -- 13.5 General Extensions
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|a 7.3 The Symmetry Diagram -- 7.4 Removing Redundant Vertices -- 7.5 Derivation of OBDD Size Equations -- 7.6 Uniqueness Argument -- 7.7 OBDDs for Tree Circuits -- 7.8 OBDD Size Summary -- 8. Difference Propagation -- 8.1 The Development of Difference Propagation -- 8.2 Deriving the Input-Output Relationships -- 8.3 The Difference Propagation Algorithm -- 8.4 The Efficiency of Differences -- 8.5 Using Functional Decomposition -- 9. Fault Model Behavior -- 9.1 Selection of Fault Models and Fault Sets -- 9.2 Fault Behavior Results and Analysis -- 10.The Contributions of Con/Obs to Test -- 10.1 Motivation to Study Con/Obs -- 10.2 Definitions of Con/Obs -- 10.3 Generating Con/Obs Information -- 10.4 Con/Obs Results and Analysis -- 10.5 Con/Obs Summary -- 11.Analyzing Test Performance -- 11.1 Defect Level Motivation -- 11.2 ATPG Model Development -- 11.3 Fault SetSelectability -- 11.4 Probabilistic Non-Target Defect Coverage -- 11.5 Faults Sets -- 11.6 Test Performance Results --
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| 653 |
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|a Computer-Aided Engineering (CAD, CAE) and Design
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| 653 |
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|a Electrical and Electronic Engineering
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| 653 |
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|a Electrical engineering
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| 653 |
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|a Computer-aided engineering
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| 700 |
1 |
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|a Mercer, M. Ray
|e [author]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
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|a The Springer International Series in Engineering and Computer Science
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| 028 |
5 |
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|a 10.1007/978-1-4615-3606-2
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| 856 |
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|u https://doi.org/10.1007/978-1-4615-3606-2?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 670.285
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| 520 |
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|a For many years, the dominant fault model in automatic test pattern gen eration (ATPG) for digital integrated circuits has been the stuck-at fault model. The static nature of stuck-at fault testing when compared to the extremely dynamic nature of integrated circuit (IC) technology has caused many to question whether or not stuck-at fault based testing is still viable. Attempts at answering this question have not been wholly satisfying due to a lack of true quantification, statistical significance, and/or high computational expense. In this monograph we introduce a methodology to address the ques tion in a manner which circumvents the drawbacks of previous approaches. The method is based on symbolic Boolean functional analyses using Or dered Binary Decision Diagrams (OBDDs). OBDDs have been conjectured to be an attractive representation form for Boolean functions, although cases ex ist for which their complexity is guaranteed to grow exponentially with input cardinality. Classes of Boolean functions which exploit the efficiencies inherent in OBDDs to a very great extent are examined in Chapter 7. Exact equa tions giving their OBDD sizes are derived, whereas until very recently only size bounds have been available. These size equations suggest that straight forward applications of OBDDs to design and test related problems may not prove as fruitful as was once thought
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