Intro to CIT 594
http://www.cis.upenn.edu/~matuszek/cit594-2008.html
Prerequisites
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The formal prerequisite is CIT 591
CIT 591 was primarily a course in Java
If you did not take CIT 591...
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You must be a reasonably good Java programmer, including
programming applications, applets, and Swing
You must be familiar with, or prepared to learn quickly:
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JUnit testing
The Eclipse IDE
You are expected to have good Java programming style
Other programming languages can not be used as a substitute
for Java
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What the course is about
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There are four main, interrelated topics in CIT594:
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In addition, we will continue to explore good programming
practices
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Recursion
Data structures
Algorithms
Analysis of algorithms
Good programming style
Good habits, such as creating test cases
Use of tools, such as NetBeans and JUnit 4
It will also be necessary to cover more Java
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Textbook #1
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This book has good
coverage of the data
structures and algorithms
that we will be using
It is intended to supplement
my lectures
Textbook #2
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I will not cover much
of this material in
class
You can read this book
at your own pace
Material from this
book will be on the
exams
Java in this course
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This is a course in algorithms and data structures, not a
second course in Java
But...
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Java 6.0 will be the primary programming language
We will study Java Collections in detail, as they are extremely
relevant to the course
You will be expected to use NetBeans 6.0 or newer
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If you have used Eclipse, you will find NetBeans to be very similar
NetBeans has an integrated profiler which we will use
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Java Collections
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Java Collections implement many of the most
important data structures for you
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A traditional data structures course would have you
implement these yourself
I don’t believe in re-inventing the wheel
However, you need to know how these data structures are
implemented, for the times when you need something more
than Java gives you
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Algorithms
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There are literally thousands of published algorithms
We will cover:
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a few algorithms that are related to the data structures we
are studying
a few more algorithms that your instructor especially likes
It’s almost always better to find an existing algorithm
than to re-invent it yourself
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Analysis of algorithms
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Analysis of algorithms is a relatively small part of this
course, but it’s an important part
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Analysis can tell you how fast an algorithm will run,
and how much space it will require
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A good algorithm, even if badly coded, can run circles
around a poor algorithm that is carefully tuned and
highly optimized
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Assignments
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Except as otherwise noted, all assignments:
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There may (or may not) be some team assignments
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Partners are assigned by the instructor
We do not have a laboratory section
You will do some assignments by yourself
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Should be done in NetBeans
Should include complete JUnit tests for non-GUI, non-I/O classes, and
Should include complete javadoc documentation for non-private entities
Must be submitted via Blackboard; email will not be accepted
You may discuss the assignments with other students
You may help (and get help with) debugging
You may not give your source code to anyone
Late assignments will lose 5 points per day, and may or may not be accepted if
more than a week late
Grading
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We will have:
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Grades will be weighted as follows:
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Approximately one assignment per week
One midterm
One final exam
Grades will be curved
We will use Blackboard to turn in assignments
50% assignments
20% midterm
30% final exam
If you feel a grading error has been made, you have one week
after grades have been posted to bring it to our attention
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Office hours and (no) labs
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I will be more available than last semester
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I avoid making appointments
I have an open door policy: If my door is open, I’m
available
Posted office hours are just the times that I try hard to be in
my office, not the only times you can talk to me
The TA will also have office hours
We will not have extra help sessions or labs this
semester
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The End
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