Faculty of Engineering Handbook

ALGORITHM AND DATA STRUCTURE

Subject Code:	ECP1026
Objective:	To provide the students with the basic understanding of algorithms and data structures for more efficient program writing.
Pre-Requisite:	ECP1016: Computer and Program Design
Credit Hours:	3
Contact Hours:	57 hours (lectures and tutorials)
Assesment:	Test/Quiz: 20% Tutorial:10 % Assignment: 10% Final Examination: 60%
Laboratory:	Supervised tutorials done in many computer labs, including Multimedia Design Lab, Multimedia Computing Lab, etc. Tutorials are mostly programming tutorials, while a few involve application of theory in paper exercises. The programming tutorials will be conducted using the GCC compiler in the LINUX operating system.
References:	I. Chai & J. D. White, "Structuring Data and Building Algorithms", McGraw-Hill, 2006 (Text Book) Kruse, Tondo & Leong, "Data Structures and Program Design in C", 2nd Edition, Prentice Hall, 1997 Kingston, "Algorithms and Data Structures: Design, Correctness, Analysis", 2nd Edition, Addison-Wesley, 1997

Course Contents

Algorithms in general
Algorithm design, comparison of algorithms, programming language independence, recursion, backtracking, look-ahead, finite state machines, Turing machines.
Data Structures
Arrays, pointers, records, linked lists, circular linked lists.
Abstract Data Types
Stacks, queues, binary trees, graphs. Implementation using arrays, linked lists, etc. Traversal of binary trees, building, inserting and deleting.
Searching and sorting
Computational cost functions, "big O", worst & average case performance of algorithms. Sequential search, binary search, hashing. Insertion sort, selection sort, merge sort, heap sort, quick sort.

Learning Outcome of Subject

At the completion of the subject, students should be able to:

explain the concept of algorithms and its application.

describe the way various types of data are represented in computers.

illustrate the basic theories and elements of computer science, such as computability, FSM, regular expressions, Turing machines, etc.

qualify an algorithm in suitable terms, such as asymptotic performance, applicability, memory consumption, simplicity, etc.

explain and correctly apply typical algorithms seen in this course, such as binary search, quicksort, introspective sort, etc.

define and correctly apply typical data structures seen in this course, such as arrays, linked lists, trees, graphs, etc.

identify the most suitable pair of algorithm and data structure(s) to be used in any particular situation.

adapt algorithms and data structures to suit new situations and applications.

use teamwork to complete any assignment involving the application of algorithms and data structures.

Programme Outcomes (% of contribution)

Ability to acquire and apply fundamental principles of science and engineering. - 40%

Capability to communicate effectively. - 5%

Acquisition of technical competence in specialized areas of engineering discipline. - 15%

Ability to identify, formulate and model problems and find engineering solutions based on a system approach. - 10%

Ability to conduct investigation and research on engineering problems in a chosen field of a study. -10%

Understanding of the importance of sustainability and cost-effectiveness in design and development of engineering solutions. - 10%

Understanding and commitment to professional and ethical responsibilities. - 5%

Capability and enthusiasm for self-improvement through continuous professional development and life-long learning. - 5%