THIS PAGE IS PROVISIONAL. Document hand1.pdf contains the LATEST
information about this course. This page will be UP-TO-DATE after the
first day of classes. Before that day, consult hand1.pdf as the information
below might be that of a previous semester.
A course on algorithms and data-structures. Methods for the analysis
of algorithms are introduced, algorithms for sorting, searching, and
selection, and data structures that support fast
and efficient information retrieval are presented
(hashing, heaps and priority queues with applications to data compression,
binary search trees, red-black trees).
Arithmetic algorithms.
Greedy algorithms and dynamic programming-based techniques are
introduced in the context of graph algorithms, arithmetic algorithms
and text compression. Graph algorithms for
traversals (depth-first, breadth-first), shortest-path problems,
and spanning tree algorithms are also introduced. String matching algorithms.
Introduction to NP-completeness.
1.1 Contact Information
INSTRUCTOR: |
Alex Gerbessiotis |
E-MAIL: |
alg435@cs.njit.edu |
OFFICE: |
GITC 4213, 4th floor |
TEL: |
(973)-596-3244 |
OFFICE HOURS: |
Tue 4:45-6:00pm and Wed 10:00-11:30am |
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OFFICE HOURS: |
By appointment Tue/Wed/Thu |
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ASSISTANT: |
TBA on course web-page |
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CLASS HOURS: |
Wed 6:00-9:05pm Rm: TIER 112 |
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Course Web Page: http://www.cs.njit.edu/~alexg/courses/cs435/index.html
The following also works: http://web.njit.edu/~alexg/courses/cs435/index.html
1.2 Course Administration
- Prerequisites
- CS 114, CS 241.
- Textbook
- T.C.Cormen, C.E.Leiserson, R.L.Rivest, and C. Stein.
``Introduction to Algorithms'', 3rt edition, McGraw-Hill, ISBN-10 : 0262033844,
(ISBN-13: 978-0262033848).
We abbreviate it in class as CLRS.
Note that a 2nd edition is also available; Differences between the two are minor,
and mainly on page numbers.
- CourseWork:
- 4 exams (including the final); programming assignments.
- Grades:
- 1000 points = PA(134)+ Ex1 (100) + Ex2 (333) + Ex3 (100) + Ex4(333).
- PA1-3
- 3 programming assignments(PAs) will be handed out. Each one
is worth 134 points. You get 134 points credit towards the final grade as
long as you collect 134 or more points from any combination of the three
PAs (you can do one, or two, or all, completely, or in part); 133 or fewer
will gain you 0 points towards the final grade.
- PA Dates
- Programs MUST be received by email before midnight of the day
indicated in the calendar. Submit early, do not wait until the very end;
you might get sick, you might get called for jury duty. The indicated date
is the last day we must receive your submission, and we will acknowledge it
promptly by email. Follow Handout 2 for compliant forms of an email submission.
No late work is accepted since one programming assignment can still satisfy
the programming assignment requirement. Plan ahead of time, and submit early.
- Practice PS
- Approximately eight problem sets PS1-8 will be
periodically posted along with their solutions. Exams 1 and 3 will draw
from these problem sets for some or all of their problems.
- Exams
- Dates in Course Calendar. Exam 1 is closed-everything.
The other three exams are open-textbook only. You may bring a copy of the
textbook but you are not allowed to borrow one during the exam.
For the final, you may also bring in class a clean copy of Handout 5
on red-black trees in addition to the textbook.
Exam1 is on Wed Feb 16, 45min, 100 points.
Exam2 is on Wed Mar 9 , 90min, 333 points.
Exam3 is on Wed Apr 13, 45mins, 100 points.
Exam4 is on Wed May 11, 2hrs, 333 points (double check with the Registrar).
- Exam Conflicts
- This is a high-numbered required course.
In case of multiple exams on a same day, this exam has priority even if it
is the last exam of the day.
2.1 Course Objectives and Outcomes
- Objective 1
- Learn how to describe the asymptotic performance of algorithms and
data structures.
- Objective 2
- Learn how to derive and determine the asymptotic performance of algorithms
and data structures.
- Objective 3
- Learn how fundamental algorithms and data-structures operate, and understand
their characteristics. Be able to choose among a variety of similar ones based on
problem/program specification and requirements.
- Objective 4
- Learn how to compose more complex algorithms using as building blocks
the fundamental algorithms introduced in class.
- Objective 5
- Learn how to compose more complex algorithms using the algorithmic
design techniques introduced in class.
- Outcome 1
- Be able to asymptotically compare functions using o,O,omega,Omega,Theta.
- Outcome 2
- Be able to solve recurrences using the master, the iteration/recursion tree,
and the substitution method.
- Outcome 3
- Become familiar with a variety of sorting algorithms and their performance
characteristics (eg, running time, stability, space usage) and be able to choose the best one
under a variety of requirements.
- Outcome 4
- Be able to understand fundamental algorithms and
data structures and be able to trace their operations for problems such as sorting, searching, selection,
operations
on numbers, polynomials and matrices, and graphs.
- Outcome 5
- Be able to identify the performance characteristics of fundamental
algorithms and data structures for problems such as sorting, searching, selection, operations
on numbers, polynomials and matrices, and graphs.
- Outcome 6
- Be able to understand fundamental algorithm design techniques and understand
how to use them to solve a variety of algorithmic problems.
- Outcome 7
- Be able to use the fundamental algorithms introduced in class to
design algorithms for more complex problems and analyze their performance.
- Outcome 8
- Be able to use the design techniques introduced in class to design
algorithms for more complex problems and analyze their performance.
2.2 Topics to be covered
T1 : AL1(1)/AL2(1)/AL3(1): Introduction, Algorithm Design Techniques (Incremental, Divide-and-Conquer)
T2 : AL1(2)/AL2(1) : Sorting Algorithms (Insertion, Selection, BubbleSort, MergeSort) Asymptotic growth of functions
T3 : AL1(3) : Recurrences
T4 : AL3(3) : Brief Review on elementary data structures (Stacks,Queues,Trees,Lists)
T5 : AL2(2),AL8(1) : HeapSort,PriorityQueues,Huffman Coding,and QuickSort(Worst-case and Average-case analysis)
T6 : AL3(2),AL8(1) : Distribution-based sorting(Count/Radix/Bucket-Sort).Lower bounds on comparison-based sorting.
T7 : AL3(3) : Selection. Selection in Linear Time.
T8 : AL3(3) : Hashing, Balanced Binary Search Trees ( Red-Black Trees).
T9 : AL2(2),AL3(1) : Dynamic Programming and Chained Matrix Multiplication,Arithmetic problems
T10: AL3(2),AL8(1) : Union Find Algorithms; Introduction to Graph Algorithms
T11: AL2(1)AL3(2) : Depth First Search,Breadth First Search,Minimum Spanning Trees.
T12: AL3(3) : Shortest path Algorithms (Dijkstra and Floyd-Warshall)
T13: AL6(3) : NP-completeness.
Section 2.2 of the previous page contains a tentative list of topics that is
intended to be covered in class. The code Ti
refers to a topic. A topic may
spread over one or more lectures. The code ALi
refers to the ACM
Computing Curricula 2001 topic description code. In parentheses, we provide
an approximate number of hours per topic. Hour coverage may change depending on
circumstances (eg. class pace, weather). Minimum time requirements of the topics covered
are. AL1 (Basic algorithmic analysis):4,
AL2 (algorithmic strategies): 6,
AL3 (fundamental computing algorithms):12,
AL6 (the complexity classes P and NP) optional.
3.1 Tentative Course Calendar
Week Wed PS/EXAM PA Comments
W1 1/19 PS1* PA1-3out Due by corresponding exam
W2 1/26 PS2* date
W3 2/2 PS3*
W5 2/9 PS4*
W4 2/16 EXAM1 PA1in MOVED to 2/23 (check web-page)
W6 2/23 PS5*
W7 3/2 PS6*
W8 3/9 EXAM2 PA2in MOVED to 3/23 (check web-page)
W- 3/16 Spring Recess; no classes
W9 3/23 PS7*
W10 3/30
W11 4/6 PS8*
W12 4/13 EXAM3 PA3in
W13 4/20
W14 4/27
W15 5/4 Reading Day 5/5 -5/11 is exam week
W16 5/11 EXAM4 5/11 is FINAL EXAM DAY
* Problem Sets (PS) with solutions are not for credit. ** In this calendar, a week starts on a Thursday
Any modifications or deviations from these dates, will be done in
consultation with the attending students and will be posted on the course Web-page.
It is imperative that students check the Course Web-page regularly and frequently.
3.2 Absenteeism
- MISSING CLASS
- If you miss a class and there is no EXAM or PA due
it's up to you to make up for lost time.
- MISSING PA
- There are three scheduled programming assignments and
only one is needed to collect the 134 points for the course. Plan ahead of
time and submit early; do not wait until the last PA or the last moment
to submit.
No extensions are granted for any reason, medical or otherwise.
- MISSING EXAM
- If you miss an exam and there is a valid documentation for
your absence, such documentation must be presented within 3 working days from
the day the reason for the absence is lifted. The maximum accommodation will
be the number of missing days to the exam date. If you miss Exam1 or Exam3,
then the Exam2 or Exam4 grade will be used respectively in such a case;
no makeup will be provided for Exams 1 and 3.
4.1 Course Policies
- Programs
- Code must be ANSI compliant and neither hardware-specific
nor OS-specific. Check Handout 2 for more information on the programming
assignments. Programming problems are graded based on test instances
decided by the grader on a test platform of the grader's choice (e.g. AFS).
Do not expect partial credit if your code fails to run on all test instances
unless you accompany your code submission with a detailed bug report.
- Extensions
- As stated earlier, no extension will be granted for the PAs
for any reason. Therefore do no try to act opportunistically i.e
skip PA1 and PA2 and aim at doing PA3 completely and correctly to
collect 134 points. You might get sick for the period leading to PA3
or called for jury duty or something else might occur and we will grant you
no extension for that, even if you have proper documentation.
- Grading
- Written work will be graded for conciseness and
correctness. Use formal arguments, be brief and to the point, and write
clearly. Material covered in class and appearing in the relevant notes
and chapters of the designated textbook can be used without proof.
Excess Programming points can be used to boost your course
grade (we account them separately).
DO NOT USE pencils to write down your solutions; if you decide to use a pencil
do not complain about grading.
- Grades
- Check the marks in written work and
report errors promptly. Resolve any issue related to Ex1-Ex3 and
PA1-3 no later than the Reading Day.
If you believe a grade you received for the solution of a problem is not
representative of your effort, talk to the grader first and then to
the instructor (if different). For programming assignments an email with
your grade is sent back to you by
replying to the email submission of the PA.
The final grade is decided based on a 0 to
1000 point scale.
A student who collects at least 500 points and completes the minimum
programming requirements should expect a grade of C or better; 800 points
or more are usually required for an A.
The instructor reserves the right to push a student's
grade up based on that student's significant programming effort.
- Incomplete
- A grade of I (incomplete) is given in rare cases
where work can not be completed during the semester
due to documented long-term illness or absence (e.g. unexpected
national guard duty). A student needs to be in good standing
(i.e. is passing the course otherwise before the absence and have
satisfied programming requirements) and receives an I if there is no time
to makeup for the documented lost time.
Not showing up in the final will probably get you an F rather than an I.
- Collaboration
- Collaboration of any kind is NOT allowed in the in-class exams.
Students who turn in code obtained through the Internet or otherwise, or is
product of another person's/student's work, risk severe punishment,
as outlined by the University. The work you submit must be the result
of your own effort.
- Mobile Devices
- Mobile phones/devices and/or laptops/notebooks MUST BE SWITCHED OFF (NOT JUST SILENCED)
before the class exams. Switch off noisy devices also before class.
- Email/SPAM
- Send email from an NJIT email address. NJIT spam filters
or us will filter other email address origins. Do not send course email
to the instructor's email address unless there is a good reason
(e.g. you don't want the grader to read the email or it's urgent and you
believe the instructor will respond faster).
Include CS 435 in the subject line then.
The NJIT Honor Code will be upheld; any violations will be
brought to the immediate attention of the Dean of Students.
Read this handout carefully!