2016 | Introduction to Algorithms and Data Structures

Undergraduate
Graduate

2016　Introduction to Algorithms and Data Structures

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Academic unit or major: Undergraduate major in Mathematical and Computing Science

Instructor(s): Watanabe Osamu Ito Toshiya Mori Ryuhei

Class Format: Lecture / Exercise

Media-enhanced courses

Day/Period(Room No.): Tue5-8(W833) Fri3-4(W833)

Group: -

Course number: MCS.T213

Credits: 3

Academic year: 2016

Offered quarter: 2Q

Syllabus updated: 2016/4/27

Lecture notes updated: -

Language used: Japanese

Access Index

Syllabus

Course description and aims

Algorithm is a core for designing software for computers, and the concept of data structure is a key to implement algorithms as computer programs. This course covers the basics of algorithms and data structures. By using concrete examples, students learn basic frameworks of algorithm design including, binary search, divide-and-conquer, dynamic programming, randomized method. Introduction to C programming language is given, and students make C programs that implement example algorithms at exercise sessions. Students also learn the concepts of basic data structures and actual ways to use these data structures in C programming. Some well-known algorithms for processing graphs and strings are given for leading students to future topics of algorithms.

Student learning outcomes

At the end of this course, students will be able to:
1) Design standard algorithms for computational tasks.
2) Implement standard algorithms as C programs by using appropriate data structures.
3) Explain the concept of efficiency of algorithms and evaluate algorithms' efficiency quantitatively.

Keywords

binary search, divide-and-conquer, dynamic programming, randomized method, linear list, heap, binary search tree, graph algorithms, string algorithms

Competencies that will be developed

✔ Specialist skills

Intercultural skills

Communication skills

Critical thinking skills

✔ Practical and/or problem-solving skills

Class flow

At the end of about two lectures, students are given exercise problems related to what is taught in the two lectures. At each exercise session, students learn how to make and execute C programs, and make programs for homework subjects.

Course schedule/Required learning

	Course schedule	Required learning
Class 1	Introduction to algorithms: Algorithms and their relation to computer hardware and software
Class 2	Algorithm description method and computational complexity	Describe an algorithm as a pseudo code and evaluate its efficiency (i.e., time complexity).
Class 3	Introduction to C programming language	Understand basic control statements and usage of arrays.
Class 4	Programming exercise: Introduction to C programming language	Make simple C programs.
Class 5	Algorithm desgin by recursion: Binary search and its recursive design, and introduction to divide-and-conqure	Understand the concept of recursion.
Class 6	Algorithm design by devide-and-conqure	Construct a recurive algorithm for some simple computational problem.
Class 7	Programming exercise: Divide-and-conqure	Programming by following the divide-and-conqure method.
Class 8	Dynamic programming (1): Memorization method
Class 9	Dynamic programming (2): Solution search	Construct an algorithm for some standard problem following recursion, memorization, and solution search steps.
Class 10	Programming exercise: Dynamic programming	Programming following the Dynamic programming technique (i.e., recursion, memorization, and solution finding method).
Class 11	Randomized algorithm	Analysis of a randomized algorithm.
Class 12	Data structure: Heap	Understand the heap structure and its efficiency.
Class 13	C programming language: record, pointer	Understand the usage of record and the notion of pointer.
Class 14	Programming exericise: Record and pointer	Programming by using records and pointers.
Class 15	Programming exericise: Advanced usage of pointers	Programming by using memory allocation commands..
Class 16	Data structure using pointer: linear list and binary search tree	Programming methods by using linear list and binary search tree.
Class 17	Programming exercise: List structure	Programming by using linear list and binary search tree.
Class 18	Hash	Analysis of hash.
Class 19	Famous algorithm (1): Shortest path algorithm	Understanding shortest path algorithms.
Class 20	Famous algorithm (2): Pattern matching algorithm	Understanding of pattern matching algorithms.
Class 21	Algorithms in practice: algorithms for control and measurement	Understanding of algorithms.for control and measurement.
Class 22	Programming exercise: C programming of practical algorithms	Programming one of the algorithms explained at classes 13, 14, and 15.

Textbook(s)

All materials used in class are provided during each class; they can be found on OCW-i after each class.

Reference books, course materials, etc.

T. Cormen, C. Leiserson, and R. Rivest,and C.Stein, Introduction to Algorithms, 3rd edition ,MIT Press, 2013, ISBN-13: 978-0262033848.

Assessment criteria and methods

Exercise problems at class (approximately 6 times) (10%)
Programming exercise problems at exercise session (5 times) (30%)
Algorithm design project homework (30%)
Final exam (30%)

Related courses

LAS.I121 ： Computer Science I
LAS.I122 ： Computer Science II
MCS.T204 ： Introduction to Computer Science

Prerequisites (i.e., required knowledge, skills, courses, etc.)

No prerequisities are necessary, but enrollment in the related courses is desirable.

Contact information (e-mail and phone) Notice : Please replace from "[at]" to "@"(half-width character).

Osamu Watanabe watanabe[at]is.titech.ac.jp
Ryuhei Mori mori[at]is.titech.ac.jp

Office hours

Contact by e-mail in advance for an appointment.

TOKYO INSTITUTE OF TECHNOLOGY