I202-ST221-Algorithms-and-Data-Structures.pdf
- 1. 1 NATIONAL UNIVERSITY OF ENGINEERING COLLEGE OF INDUSTRIAL AND SYSTEMS ENGINEERING SYSTEMS ENGINEERING PROGRAM SYLLABUS - ST221 ALGORITHMS AND DATA STRUCTURES I. GENERAL INFORMATION CODE : ST221 Algorithms and Data Structure SEMESTER : 2 CREDITS : 3 HOURS PER WEEK : 4 (Theory – Practice - Laboratory) PREREQUISITES : CB121 Differential Calculus CONDITION : Compulsory II. COURSE DESCRIPTION The course prepares students for the formulation of algorithms to solve different problems in mathematics and engineering. Students understand and apply different types of data structures and develop algorithms for arrays processing based on sorting, ordering, searching using different selective, sequential and repetitive control structures. Algorithms and program optimization criteria are analyzed in terms of processing and resources requirements, simplicity and efficiency. Intensive analysis of algorithms and their computer implementation is promoted throughout the course. III. COURSE OUTCOMES At the end of the course, students: 1. Develop algorithms as a set of instructions to solve problems using computing methods. 2. Understand the meaning and scope of different types of data structures and apply them according to the characteristics of the problem being solved. 3. Develop computer programs using multi-dimensional arrays, loops, and sequential, selective and repetitive control structures, recursion. 4. Considers program optimization criteria in terms of processing requirements, execution times, memory and resources requirements. 5. Develop structured and object oriented computer programs. IV. LEARNING UNITS 1. PROBLEMS, ALGORITHMS AND PROGRAMS Introduction to problems, algorithms and programs / Methodologies for problem solving / Techniques for algorithms formulation / Algorithms specification: Imperative, functional / Algorithm complexity analysis: efficiency, complexity / Recurrence equations / Non-recursive algorithm complexity / Recursive complexity algorithms. 2. PSEUDO-CODE PROGRAMMING Variables / Local and global variables / Sequential control structures / Selective control structures: simple, multiple, nested / Repetitive control structures / Fixed number of repetition loops / Loop break conditions / Controlled input loops/ Controlled output loops / Nested loops. 3. ALGORITHMS DESIGN TECHNIQUES Vectors and matrices / Vector operations / Matrix operations / Chains: creation, use and operations / Chain arrays / Pointers / Algorithms / Brute force method / Recursion / Divide and win / Dynamic programming / Voracious algorithms / Input and output. 4. SEARCH AND ORDERING METHODS
- 2. 2 Bubble method / Direct insertion method / Shell sort method / Heap sort method / Quick sort method / Merge sort methods / Applications. 5. PROGRAMMING LANGUAGE FOR DATA STRUCTURE Modular programming / Object oriented programming / Design patterns / Heritage and polymorphism / Data types in execution time / Interfaces /Execution faults: classification representation and treatment / Fault-tolerant software / Applications. 6. DYNAMIC PROGRAMMING Pointers: creation, use / Pointer operations / Hierarchical data structures / Multipath hierarchical data structures / Network-type data structures / Graphs / Simple linked lists / Ordered linked lists / Doubled link lists / Trees / Search binary trees / Queues / Applications. V. LABORATORIES AND PRACTICAL EXPERIENCES: Laboratories using C++ language: Laboratory 1: Introduction algorithms Laboratory 5: Ordering methods Laboratory 2: Algorithms complexity Laboratory 6: Object oriented programs Laboratory 3: Algorithms design techniques Laboratory 7: Linked lists Laboratory 4. Algorithms design techniques Laboratory 8: Double linked lists VI. METHODOLOGY This course is carried out in theory, practical and lab sessions. In theory sessions, the instructor introduces concepts, theorems and applications. In practical sessions, different problems are solved and their solutions are analyzed. In laboratory sessions, students implement the algorithms using PSelnet and C languages. At the end of the course, students must submit and defend an integrating project. In all sessions, students’ active participation is encouraged. VII. EVALUATION FORMULA Evaluation system F. The average grade PF is calculated as follows: PF = (EP + EF + 2 PP)/4 EP: Mid-Term Exam EF: Final Exam PP: Quizzes average (4 and 1 is eliminated) VIII. BIBLIOGRAPHY 1. M.A. WEISS Data Structures and Algorithms. Analysis in Java. Addison Wesley, 2010. 2. D. MALIK Data Structures Using C++ Thomson Learning, 2014. 3. L. JOYANES and I. ZAHONERO Data Structures in Java. McGraw Hill, 2008