Class notes
CS 610 Introduction to Data Structures Lecture Notes
- Course
- CS 610
- Institution
- New Jersey Institute Of Technology
This is a comprehensive and detailed note on introduction to data structures and algorithms.
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A. V. GERBESSIOTISCS610
Spring 2022 December 22, 2021
Introduction: Course outline
Page 1 Document 0
Welcome to CS610 (Face to Face section)!
This Document 0 is the Course Outline. Document 0 is not the syllabus. The Syllabus is
Document 1. All documents would become available in canvas Announcements. NJIT uses the
Learning Management System (LMS) known as canvas.
1 Course Delivery
Delivery in this course is through
(1) Lectures explaining TEXTBOOK content and instructor’s typewritten notes i.e. Subjects.
(2) The canvas LMS.
(3) A course web-page (CWP).
(4) Email (webmail, not canvas messaging).
(5) Other supplementary material (handwritten notes of the instructor used in class).
1.1 Lectures on Subjects
Lectures delivered in class are based on the textbook and supplemented by instructor typewritten
notes, known as Subjects. Handwritten notes used in class by the instructor are also provided.
1.2 Canvas
The URL (Uniform Resource Locator) of the LMS is canvas.njit.edu. Access requires myUCID
credentials (login, password). Renew credentials NOW if they are to expire during the semester.
1.3 Course web-page
http://www.cs.njit.edu/∼alexg/courses/cs610/index.html
The course web-page (CWP from now) is split into three sections: A (Announcements, different
from canvas Announcements), B (Public Information), and C (Other). Section C requires creden-
tials that are common to all students. For login use cs610 and password use 2022spring
1.4 Course email: webmail
The instructor’s email address is alexg+cs610@njit.edu. Read the email protocol used in the
course FAQ (last page of this document). Do not use canvas messaging or canvas email; it is rarely
read and is not NJIT sanctioned: your email will be lost.
1.5 Supplementary material
In emergencies Webex Recordings would be made available in canvas Modules. Kaltura voiceovers
might be made available for material not in the textbook and in the PrP.
, A. V. GERBESSIOTIS
CS610
Spring 2022 December 22, 2021
Introduction: Course outline
Page 2 Document 0
2 Course Structure
2.A. Textbook information is available in the Syllabus (Document 1).
2.B Subjects are supplemental typewritten notes authored by this instructor. They provide
detail not found in the textbook for some topics. Some prerequisite material (Discrete Math) is
very briefly listed for the sake of completeness and to provide definitions when needed. The cover
page of a Subject indicates the chapters of the designated textbook it draws from.
2.C Practice Problem Sets (PS). Most Subjects have a matching problem set (eg Subject 1
has PS1) that contains practice problems (past homework and exam problems) with solutions or
hints of a solution. The PSs are in canvas Modules at the very bottom of the scrollable area there.
2.D Homeworks in canvas. A Homework (HW) is for credit and set-up as an untimed, limited
availability canvas Quiz, with no more than three attempts to submit but only the LAST AT-
TEMPT graded. A HW is due before noon (12 o’clock noon which is canvas’s 12PM) on a day
(possibly non class-day) specified Document 1 (Syllabus). See Document 3 for canvas Quiz terms.
2.E Programming Project. Assignments. A Programming Project is for credit in this class.
A grave mistake students make is to not follow the directions of Document 4 and a worse mistake
is to never test their intended submission on an NJIT *NIX machine. Furthermore, programming
assignments are given: they are not for credit and are not graded. Practice makes better.
2.1 BEFORE A CLASS
• Anticipate what will be covered in that class. (We provide guidance before the first class.)
• Study the relevant sections of the designated textbook along with the relevant Subject.
• Prepare questions to ask. Keep notes.
2.2 DURING A CLASS
• Relate the material covered in class with the studied material. If the emphasis in class is on
different topics than your prior study of the material, mark topics for a follow-up review.
• Ask questions. We learn from mistakes! Keep notes.
2.3 AFTER A CLASS
• Review the material covered in class. Write-down all computational problems introduced and
all algorithms with their data structures described in class and their properties (eg running
time). Implement them to understand them better. Practice makes perfect!
• If there is a PS for the Subject, practice with it. If there is a HW, do it!
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