How to think about algorithms /
Edmonds, Jeff, 1963-
How to think about algorithms / Jeff Edmonds. - Cambridge ; New York : Cambridge University Press, 2008. - xiii, 448 p. : ill. ; 25 cm.
Includes index.
Part I. Iterative Algorithms and Loop Invariants: 1. Measures of progress and loop invariants; 2. Examples using more of the input loop invariant; 3. Abstract data types; 4. Narrowing the search space: binary search; 5. Iterative sorting algorithms; 6. Euclid's GCD algorithm; 7. The loop invariant for lower bounds; Part II. Recursion: 8. Abstractions, techniques, and theory; 9. Some simple examples of recursive algorithms; 10. Recursion on trees; 11. Recursive images; 12. Parsing with context-free grammars; Part III. Optimization Problems: 13. Definition of optimization problems; 14. Graph search algorithms; 15. Network flows and linear programming; 16. Greedy algorithms; 17. Recursive backtracking; 18. Dynamic programming algorithms; 19. Examples of dynamic programming; 20. Reductions and NP-completeness; 21. Randomized algorithms; Part IV. Appendix: 22. Existential and universal quantifiers; 23. Time complexity; 24. Logarithms and exponentials; 25. Asymptotic growth; 26. Adding made easy approximations; 27. Recurrence relations; 28. A formal proof of correctness; Part V. Exercise Solutions.
9780521849319 (hardback) 0521849314 (hardback) 9780521614108 (pbk.) 0521614104 (pbk.)
Algorithms
Loops (Group theory)
Invariants
Recursion theory--Study and teaching.--Study and teaching.--Study and teaching.--Study and teaching.
518.1 / EDM
How to think about algorithms / Jeff Edmonds. - Cambridge ; New York : Cambridge University Press, 2008. - xiii, 448 p. : ill. ; 25 cm.
Includes index.
Part I. Iterative Algorithms and Loop Invariants: 1. Measures of progress and loop invariants; 2. Examples using more of the input loop invariant; 3. Abstract data types; 4. Narrowing the search space: binary search; 5. Iterative sorting algorithms; 6. Euclid's GCD algorithm; 7. The loop invariant for lower bounds; Part II. Recursion: 8. Abstractions, techniques, and theory; 9. Some simple examples of recursive algorithms; 10. Recursion on trees; 11. Recursive images; 12. Parsing with context-free grammars; Part III. Optimization Problems: 13. Definition of optimization problems; 14. Graph search algorithms; 15. Network flows and linear programming; 16. Greedy algorithms; 17. Recursive backtracking; 18. Dynamic programming algorithms; 19. Examples of dynamic programming; 20. Reductions and NP-completeness; 21. Randomized algorithms; Part IV. Appendix: 22. Existential and universal quantifiers; 23. Time complexity; 24. Logarithms and exponentials; 25. Asymptotic growth; 26. Adding made easy approximations; 27. Recurrence relations; 28. A formal proof of correctness; Part V. Exercise Solutions.
9780521849319 (hardback) 0521849314 (hardback) 9780521614108 (pbk.) 0521614104 (pbk.)
Algorithms
Loops (Group theory)
Invariants
Recursion theory--Study and teaching.--Study and teaching.--Study and teaching.--Study and teaching.
518.1 / EDM