Data structures and algorithms in C++ / Adam Drozdek
By: Drozdek, Adam.
Material type:
BookPublisher: New Delhi: Cenage Learning, 2012Edition: 3rd edition.Description: xvi. 758 p.ISBN: 978-8131501153; 8131501159.Subject(s): C (Computer program language) | Java (Computer program language)DDC classification: 005.133 D793D 2012 | Item type | Current location | Collection | Call number | Status | Date due | Barcode | Item holds |
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Books
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Information Technology University, Lahore General Stacks | Non-fiction | 005.133 D793D 2012 (Browse shelf) | Available | 000713 |
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| 005.133 D325V 2018 Visual C# : | 005.133 D528C 2010 C programming essentials : \ K.N Dey | 005.133 D793D 2012 Data structures and algorithms in java\ Adam Drozdek | 005.133 D793D 2012 Data structures and algorithms in C++ / | 005.133 D793D 2012 c.2 Data structures and algorithms in Java / | 005.133 D815M 2015 MySQL / | 005.133 E191T 2013 v.1 Thinking in C++: |
Strengthen your understanding of data structures and their algorithms for the foundation you need to successfully design, implement and maintain virtually any software system. Theoretical, yet practical, DATA STRUCUTRES AND ALGORITHMS IN C++, 4E by experienced author Adam Drosdek highlights the fundamental connection between data structures and their algorithms, giving equal weight to the practical implementation of data structures and the theoretical analysis of algorithms and their efficiency. This edition provides critical new coverage of treaps, k-d trees and k-d B-trees, generational garbage collection, and other advanced topics such as sorting methods and a new hashing technique. Abundant C++ code examples and a variety of case studies provide valuable insights into data structures implementation. DATA STRUCTURES AND ALGORITHMS IN C++ provides the balance of theory and practice to prepare readers for a variety of applications in a modern, object-oriented paradigm.
Previous ed., Cambridge, Mass. : Course Technology, 2005.
Includes Index
1. Object-Oriented Programming Using C++. 2. Complexity Analysis. 3. Linked Lists. 4. Stacks and Queues. 5. Recursion. 6. Binary Trees. 7. Multiway Trees. 8. Graphs. 9. Sorting. 10. Hashing. 11. Data Compression. 12. Memory Management. 13. String Matching. Appendix A: Computing BIG-O. Appendix B: Algorithms in the Standard Template Library. Appendix C: NP-Completeness.
Theoretical, yet practical, this book highlights the fundamental connection between data structures and their algorithms, giving equal weight to the practical implementation of data structures and the theoretical analysis of algorithms and their efficiency. It prepares readers for a variety of applications in a modern, object-oriented paradigm.
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