CSE2003 Data Structures and Algorithms (original) (raw)
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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.
Data structures & their algorithms
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...
Data Structures and Algorithms
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A collection of values that share a common set of operations is called a data type. Structured or composite data types are collections of individual data items of the same or different data types. Data structures are collections of variables, possibly of different data types, connected in various ways. High-level languages prior to Pascal usually limited their concepts of data types to those provided directly by hardware (integers, reals, double precision integers and reals, and blocks of contiguous locations). Two objects had different types if it was necessary to generate different code to manipulate them. Pascal and later languages have taken a rather different approach, based on the concept of abstract data types. An abstract data type is a programming language facility for organizing programs into modules using criteria that are based on the data structures of the program. Also, an abstract data type can be defines as a set of values and a set of procedures that manipulate those values. The specification of the module should provide all information required for using the type, including the allowable values of the data and the effects of the operations. However, details about the implementation, such as data representations and algorithms for implementing the operations, are hidden within the module. This separation of specification from implementation is a key idea of abstract data types.
Lecture Notes Data Structures CSC 214
With a dynamic learn-by-doing focus, this document encourages students to explore data structures by implementing them, a process through which students discover how data structures work and how they can be applied. Providing a framework that offers feedback and support, this text challenges students to exercise their creativity in both programming and analysis. Each laboratory work creates an excellent hands-on learning opportunity for students. Students will be expected to write C-language programs, ranging from very short programs to more elaborate systems. Since one of the goals of this course is to teach how to write large, reliable programs. We will be emphasizing the development of clear, modular programs that are easy to read, debug, verify, analyze, and modify. PREREQUISITE: A good knowledge of c-language, use of Function and structures.