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| Contributors | |
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| Preface | |
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| The State of Artificial Intelligence | |
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| Introduction | |
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| Rule-Based Systems | |
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| Moving Beyond Rules | |
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| Intelligent Agents | |
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| Genetic Algorithms | |
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| Neural Networks | |
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| Hybrid Systems | |
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| Conclusions | |
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| Acknowledgements | |
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| References | |
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| Software Model Checking with Spin | |
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| Introduction | |
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| Background | |
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| Finite Automata | |
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| Temporal Logic | |
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| LTL Model Checking | |
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| Model Extraction and Abstraction | |
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| Perspective | |
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| Acknowledgements | |
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| References | |
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| Early Cognitive Computer Vision | |
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| Introduction | |
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| Visual Measurements | |
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| Invariance | |
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| Natural Image Statistics | |
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| Conclusions | |
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| References | |
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| Verification and Validation and Artificial Intelligence | |
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| Introduction | |
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| AI Software Can Be Complex | |
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| Model-Based AI Systems | |
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| The Knowledge Level | |
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| AI Software Can Be Nondeterministic | |
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| Adaptive AI Systems | |
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| Conclusion | |
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| Acknowledgements | |
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| References | |
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| Indexing, Learning and Content-Based Retrieval for Special Purpose Image Databases | |
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| Introduction | |
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| Representation of Image Content: Feature Extraction | |
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| Detection of Salient Design Image Elements by Figure-Ground Segregation | |
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| MPEG-7 Description of Design Images | |
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| Inference and Learning for Relevance Feedback by Examples | |
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| Conclusion and Outlook | |
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| Acknowledgements | |
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| References | |
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| Defect Analysis: Basic Techniques for Management and Learning | |
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| Introduction | |
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| Modeling for Quality Management | |
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| Monitoring Process Performance | |
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| Learning and Improvement | |
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| Summary and Conclusions | |
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| References | |
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| Function Points | |
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| Introduction | |
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| Albrecht/IFPUG Function Points | |
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| Experience with IFPUG Function Points | |
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| Mark II Function Points | |
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| Some Other Early Variations | |
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| COSMIC | |
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| Function Points for Object-Oriented Software | |
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| Function Point Standards | |
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| Conclusions | |
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| Acknowledgements | |
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| References | |
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| The Role of Mathematics in Computer Science and Software Engineering Education | |
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| Introduction | |
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| Mystery Novels and John Wooden | |
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| Computer Science and Software Engineering | |
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| Foundational Mathematics | |
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| Models | |
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| General Mathematical Reasoning | |
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| Patterns, It Is All About Patterns | |
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| Inductive Thinking and Generalization | |
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| Declarative Versus Imperative Reasoning | |
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| Algorithmic Problem Solving | |
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| Recursive Thinking | |
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| Mathematical Induction | |
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| Why Mathematics? | |
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| Curricula Issues | |
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| Foundations of Computing-A First Course | |
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| Conclusions | |
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| Acknowledgements | |
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| CSE-113 Foundations of Computer Science I | |
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| Butler University, Foundations of Computing I | |
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| Sample First Exam for Foundations of Computing I (100 minutes) | |
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| Representative List Processing Lab Exercises Using Standard ML | |
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| Solutions for Problems Cited | |
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| References | |
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| Author Index | |
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| Subject Index | |
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| Contents of Volumes in This Series | |