holy angel university

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Page 1 of 8 AY1617 – July 15, 2016 /ccaro

HOLY ANGEL UNIVERSITY

COLLEGE OF INFORMATION AND COMMUNICATIONS TECHNOLOGY DESIGN AND ANALYSIS OF ALGORITHMS

COURSE SYLLABUS

Course Code : 6DEALGO Prerequisite : 6DS

Course Credit : 3 Units (3 hours LEC) Year Level: 3^rd year

Degree Program : Bachelor of Science in Computer Science (BSCS) Course Description :

This course introduces the basic algorithmic analysis and strategies. It focuses on the principles of algorithms, its design and analysis. Fundamental ideas of algorithm analysis and design strategies will be covered. Throughout the course, different algorithm design strategies will be presented. Students are expected to know how to specify algorithm and apply design strategies to any computing problems

At the end of the course, students will be able to:

Course Outcomes Graduate Outcomes Aligned to C1 Identify and define the fundamentals of

analysis of algorithm efficiency, know the algorithms performance, synthesize and decide when an algorithmic design situation calls for it. Based on the following paradigms:

(1) Brute force

(2) Decrease and conquer (3) Divide and conquer (4) Transform and conquer (5) Greedy technique (6) Dynamic Programming (7) Space and Time Trade-Offs

BSCS01: Apply knowledge of computing, science and mathematical foundations, algorithmic principles and computer science

BSCS01.1: Defend using sound science and fundamentals

BSCS02: Identify, analyze, formulate, research literature, and solve complex computing problems and requirements reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines

BSCS02.2: Adapt on practices and standards applicable to the problem domain

BSCS02.4: Translates verbal problems into mathematical algorithms so as to construct valid arguments using the accepted symbolic system of mathematical reasoning to determine extent of information needed.

C2 Incorporate the different data structures in order to formulate the best data

BSCS03: Design and evaluate solutions for complex computing problems, and design and evaluate systems, components, or processes that meet

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structures needed for the problem.

Evaluate the different ways to analyze algorithms (expected running time, probability of error)

Select an appropriate data structure for a particular design situation.

specified needs

BSCS03.1: Formulate set of alternative solutions to address complex computing problems

BSCS05: An ability to apply mathematical foundations, algorithmic principles and computer science

BSCS05.1: Decide on the use of appropriate algorithms for development of software where the balance on logic and efficiency is kept.

Learning Evidence

As evidence of attaining the above learning outcomes, the student has to do and submit the following:

LE1 Research Project

The research project involve a real life computing case which will assess how the student will make choices of algorithms to use to address requirements needed to solve the computing problem.

Based on the following :

 Prove the correctness and analyze the running time of the basic algorithms for those classic problems in various domains;

 Apply the algorithms and design techniques to solve problems;

 Analyze the complexities of various problems in different domains.

C1, C2

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Measurement System (LE1)

To assess the level of performance in the learning evidences, the following rubrics will be used:

LE1: Research Project

Area to Assess Point Value

Correctness of Algorithm 30

Critical Thinking 30

Style and Mechanism (documentation) 20

Organization 20

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Learning Plan:

In order to achieve the outcomes of this course, learners will go through this learning plan.

Intended Learning Outcome

Unit#

(weeks)

Course Outcome

Topic Learning Activities Assessment Activity

Student Output Define the

meaning of algorithm Understand the fundamentals ideas of algorithmic problem solving Differentiate and know the

efficiency analysis and different asymptotic notations Distinguish the analysis between non – recursive and recursive algorithms Identify the

different algorithm design technique Differentiate the different sorting, searching techniques

1 -5 CO1 Algorithm

Fundamentals of Algorithmic Problem Solving

Problem types

Fundamentals of the Analysis of Algorithm efficiency

Analysis framework Asymptotic notations

Mathematical analysis of recursive and non – recursive algorithms

Brute force

 Selection sort and Bubble sort

 Sequential search and Brute Force string notation

 Exhaustive search

Lecture Discussion Oral Recitation

Mastery and application test (oral/written)

Required Activity

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Unit#

(weeks)

Student Output

Recognize the dissimilarity of the appropriate

algorithm based on the efficiency analysis

Decide what appropriate technique is to be use in designing an correct algorithm

Divide and conquer

 Merge sort

 Quick sort

 Binary Search

 Binary tree traversal and related properties

6 Prelim

Examination Identify the

different algorithm design technique Differentiate the different sorting, searching techniques Recognize the dissimilarity of the appropriate

7-11 CO1, CO2

Decrease and conquer

 Insertion sort

 Depth – First Search and Breadth – First Search

 Topological sorting

 Decrease – by – a – constant factor algorithm

 Variable Size Decrease algorithm

Transform and conquer

 Presorting

 Gaussian Elimination

 Balanced Search Trees

Lecture Discussion Oral Recitation Research Brain Storming

Activity and Seatwork for application of different algorithms

Proposal for Research Project (LE1)

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Unit#

(weeks)

Student Output

Decide what appropriate technique is to be use in designing an correct algorithm

 Heaps and Heap sort

 Horner’s rule and Binary Exponentiation

 Problem Reduction

12 Midterm

Examination

Identify the

different algorithm design technique Differentiate the different sorting, searching techniques Recognize the dissimilarity of the appropriate

Decide what appropriate technique is to be

13 - 17 Space and Time Trade-Offs

 Input enhancement in string matching

 Hashing

 B-Trees

Dynamic Programming

 Warshall’s Algorithm

 Floyd’s Algorithm

 Optimal Binary Search Tree

 The knapsack problem and memory functions Greedy technique

 Prim’s Algorithm

 Kruskal’s Algorithm

 Dijkstra’s Algorithm

 Huffman Trees

Lecture Discussion Oral Recitation Research Brain Storming

Activity and Seatwork for application of different algorithms

Research Project (LE1)

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Unit#

(weeks)

Student Output use in designing

an correct algorithm

18 Final

Examination

Course References:

A. Published Materials

 Introduction to the Design and Analysis of Algorithms, 3^rd Edition Levitin, Anany (2012)

 Hyperspectral Data Processing : Algorithm Design and Analysis Chang, Chein-I (2013)

 Algorithms by Dasgupta, Sanjoy (2008)

 Algorithms by Johnsonbaugh, Richard (2004)

B. Web References

 http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=IntroToAlgorithms (Design and Analysis of Algorithms by Prof. Tim Roughgarden)

 http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-046j-design-and-analysis-of-algorithms- spring-2012/ (Design and Analysis of Algorithms Open Courseware)

 https://www.coursera.org/course/algo (Algorithms: Design and Analysis)

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Grading System

The final grade in this course will be composed of the following items and their weights in the final grade computation:

Class Standing 70%

Major Exam 30%

FINAL GRADE = Class Standing + Major Exam Transmutation Table:

Minimum Passing Percent Average of Subject : 50

RANGE EQUIVALENTS (COMPUTED AVERAGES & TRANSMUTED VALUES)

Range of Computed Average Range of

Transmuted Values Grade General Classification

94.0000 100.0000 97 100 1.00 Outstanding

88.0000 93.9999 94 96 1.25 Excellent

82.0000 87.9999 91 93 1.50 Superior

76.0000 81.9999 88 90 1.75 Very Good

70.0000 75.9999 85 87 2.00 Good

64.0000 69.9999 82 84 2.25 Satisfactory

58.0000 63.9999 79 81 2.50 Fairly Satisfactory

52.0000 57.9999 76 78 2.75 Fair

50.0000 51.9999 75 3.00 Passed

Below Passing Average 5.00 Failed

Failure due to absences 6.00 FA

Unauthorized Withdrawal 8.00 UW

Officially Dropped 9.00 Dropped