Preface<BR>AcknowledgmentsPART I. PRELIMINARIES <BR>1. Introduction And Historical Review <BR>or, What's It All About? <BR>2. Algorithms And Data <BR>or, Getting It Done <BR>3. Programming Languages and Paradigms<BR>or, Getting It Done by Computer <BR>PART II. METHODS AND ANALYSIS <BR>4. Algorithmic Methods <BR>or, Getting It Done Methodically <BR>5. The Correctness of Algorithms <BR>or, Getting It Done Right <BR>6. The Efficiency of Algorithms <BR>or, Getting It Done Cheaply <BR>PART III. LIMITATIONS AND ROBUSTNESS <BR>7. Inefficiency and Intractability <BR>or, You Can't Always Get It Done Cheaply <BR>8. Noncomputability and Undecidability <BR>or, Sometimes You Can't Get It Done At All! <BR>9. Algorithmic Universality and Its Robustness <BR>or, The Simplest Machines That Get It Done <BR>PART IV. RELAXING THE RULES <BR>10. Parallelism, Concurrency and Alternative Models<BR>or, Getting Lots Of Stuff Done at Once<BR>11. Probabilistic Algorithms <BR>or, Getting It Done by Tossing Coins <BR>12. Cryptography and Reliable Interaction<BR>or, Getting It Done in Secret<BR>PART V. THE BIGGER PICTURE<BR>13. Software Engineering<BR>or, Getting It Done When It's Large<BR>14. Reactive Systems<BR>or, Getting It to Behave Properly Over Time<BR>15. Algorithmics And Intelligence <BR>or, Are They Better at It Than Us? Postscript<BR>Selected Solutions<BR>Bibliographic Notes<BR>Index