1. Introduction.- 1.1 Program Understanding.- 1.2 The State of The Practice.- 1.3 Conceptual Program Understanding.

- 1.4 The Remainder of This Book.- 2. Plan-Based Program Understanding.- 2.1 Overview.- 2.2 Ast-Based Approaches.

- 2.3 Graph-Based Approaches.- 2.4 Analysis of Previous Approaches.- 3. Program Understanding and Constraint Satisfaction.- 3.1 Introduction.

- 3.2 Constraint Satisfaction Problems.- 3.3 Program Understanding as Constraint-Satisfaction.- 3.4 Modeling Existing Program Understanding Algorithms.- 4. Initial Experiments with Concept Recovery.

- 4.1 Introduction.- 4.2 Experimental Framework.- 4.3 Experiments With Csp Solvers.- 4.4 Comparing Existing Approaches.

- 4.5 Summary of Results.- 5. Additional Experiments with Concept Recovery.- 5.1 Introduction.- 5.2 Experimental Framework.

- 5.3 Some Experiments With "Real" Programs.- 5.4 Experiments with Domain-Value Pre-Filtering.- 5.5 Experiments With A New Constraint-Based Algorithm.- 5.6 Summary.

- 6. Program Understanding and AI Plan Recognition.- 6.1 Introduction.- 6.2 An Ai Approach to Plan Recognition.- 6.3 Problems with Applying AI Plan Recognition.

- 6.4 Layered Map-CSP Versus the AI Approach.- 7. Improving our Constraint-Based Approach.- 7.1 Introduction.- 7.2 Addressing Problems with Layered Map-Csp.

- 7.3 Integrated Understanding: PU-CSP.- 7.4 Solving Strategies for PU-CSP.- 7.5 PU-CSP Versus Layered MAP-CSP.- 8. Conclusions.

- 8.1 Summary.- 8.2 Future Experiments.- 8.3 Future Modeling and Algorithm Development.- 8.4 Future Tool Development.

- 8.5 Applying Plan Recognition to the Year 2000 Problem.- 8.6 Contributions to Artificial Intelligence.- 8.7 Final Remarks.- References.