Data structures and algorithms

COSC 302 surveys the most important algorithms and data structures in use in our digital world. Particular emphasis is given to algorithms for sorting, searching, and string processing. Fundamental algorithms in a number of other areas are basic data structure operations are covered. The course will concentrate on developing implementations, understanding their performance characteristics, and estimating their potential effectiveness in applications. File system organization and access methods. Course projects require advanced problem-solving, design, and implementation skills.

1991

I. INTRODUCTION PROGRAMMING AS AN ENGINEERING ACTIVITY. Computer Science Background. Memory and Data in Von Neuman Computers. Notation for Programs Locatives. Abstract Data Types. Mathematical Background. Finite and Infinite Series. Logarithms, Powers, and Exponentials. Order Notation. Recurrence Relations. Naive Probability Theory. II. ALGORITHM ANALYSIS. Properties of an Algorithm. Effectiveness Correctness. Termination Efficiency. Program Complexity. Exact vs. Growth-Rate Analysis. Principles of Mathematical Analysis. Expected Case and Amortized Analysis. Algorithm Paradigms. Brute-Force and Exhaustive Search. Greedy Algorithms. Dynamic Programming. NP Completeness. III. LISTS. List Operations. Basic List Representations. Stack Representation in Contiguous Memory. Queue Representation in Contiguous Memory. Stack Representation in Linked Memory. Queue Representation in Linked Memory. Stacks and Recursions. List Representations for Traversals. Doubly Linked Lists. IV. TREES BASIC D...

Proceedings 11th International Parallel Processing Symposium, 1997

We present a parallel priority data structure that improves the running time of certain algorithms for problems that lack a fast and work-e cient parallel solution. As a main application, we give a parallel implementation of Dijkstra's algorithm which runs in O(n) time while performing O(m log n) work on a CREW PRAM. This is a logarithmic factor improvement for the running time compared with previous approaches. The main feature of our data structure is that the operations needed in each iteration of Dijkstra's algorithm can be supported in O(1) time.

A.R.S. Publications, Chennai, 2022

(CD3291 – Data Structures and Algorithms & CD3281 – Data Structures and Algorithm Laboratory - B. Tech. – Information Technology - As per the Latest Syllabus of Anna University, Chennai - Regulation 2021) This book "Data Structures and Algorithms" is about basic idea towards data representation in program and its manipulation. It provides a clear view towards Abstract Data Type and Object-Oriented Programming on Python. It provides a preliminary study on linear data structures, sorting, searching, hashing, Tree and Graph Structures along with Python implementation. Unit I: Introduction towards Abstract Data Types and Object-Oriented Programming. Contributes a knowledge on analysis of algorithm, asymptotic notations, divide & conquer and recursion with example. Unit II: Summary on Linear structures and its working mechanism. Provides an hands on understanding towards the Array List, Linked List, Stack and Queue. Linked list were represented with singly, doubly, circularly, stack and queue through Python. Unit III: Brief knowledge over sorting and searching. Bubble, Selection, Insertion, Merge, Quick sort implemented through Python. It provides detailed understanding and procedures for linear search, binary search, hash functions and collision handling. Unit IV: Transitory awareness on Tree and its traversal. Provides a procedure in Python to construct Binary Tree, AVL Tree, Heap, B Tree & B+ Tree and Tree Traversal. Unit V: Provides a study over graph and its traversal mechanisms. Python hands on experience over estimating shortest path and constructing minimum spanning tree over a graph. Understanding towards problem complexity and its classes. Unit VI: It provides an implementation idea over recursive algorithm, List, Stack and Queue. Understanding towards the several sorting and searching algorithm using python. Detailed implementation to construct tree traversal, minimum spanning tree and estimate the shortest path on graph through Python.

Mathematical Systems Theory, 1976

We present a data structure, based upon a hierarchically decomposed tree, which enables us to manipulate on-line a priority queue whose priorities are selected from the interval 1,..., n with a worst case processing time of (9 (log log n) per instruction. The structure can be used to obtain a mergeable heap whose time requirements are about as good. Full details are explained based upon an implementation of the structure in a PASCAL program contained in the paper. * Work supported by grant CR 62-50. Netherlands Organization for the Advancement of Pure Research (Z.W.O.). 100 P. VAN EMDE BOAS, R. KAAS AND E. ZIJLSTRA

Lecture Notes in Computer Science, 1981