CS 312 Overview

What is CS312 About?

CS312 is the third programming course in the Computer Science curriculum, following CS100 and CS211.  The goal of the course is to help students become excellent programmers and software designers who can design and implement software that is elegant, efficient, and correct, and whose code can be maintained and reused.

Topics

CS312 covers a broad set of topics, including:

• Alternative programming paradigms, especially functional and concurrent programming
• Writing specifications that support modular programming
• Reasoning about program behavior and performance
• Type systems and data abstraction
• The design and implementation of programming languages

Contacting the course staff

The best way to reach the course staff is by posting questions or comments to the CS312 newsgroup cornell.class.cs312. We will try to respond to questions on a regular basis. However, the newsgroup is not meant to replace office hours. Please do not expect prompt answers during the weekend, or the evening an assignment is due. You can also reach the course staff by sending email to Turn on JavaScript to view email address . If we judge that the question might have been better directed to the newsgroup, the question may be forwarded there unless an explicit request is included to the contrary.

Please read these guidelines before emailing or using the newsgroups.

Course Staff

Lectures and Recitations

Lectures: Tuesday and Thursday, 10:10-11:00, 203 Thurston Hall. Attendance is required.

Recitations: Monday and Wednesday. Attendance is required; students will be responsible for the new material presented in recitation. Students may attend sections other than the one they are assigned to.

Notes for most lectures and recitations are available from the course schedule.

Functional programming in SML

We use a programming language from the ML family of programming languages throughout the course: Standard ML (SML). SML is a modern functional programming language with an advanced type and module system.   The course is not about programming in SML.  Rather, SML provides a convenient framework in which we can achieve the objectives of the course.  Like the object-oriented model of Java, the functional paradigm of SML is an important programming model with which all students should be familiar, as it underlies the core of almost any high-level programming language. In addition the SML type and module systems provide frameworks for ensuring code is modular, correct, re-usable, and elegant.  Other languages, such as Java, also provide facilities to achieve these goals, but the mechanisms of SML are largely orthogonal to those of object-oriented languages.  By studying alternatives, students will be better equipped to use, implement or even design future programming environments that combine the best features of both worlds.

Another important reason we use SML is that it has a relatively clean and simple model that makes it easier to reason about the correctness of programs.  In our studies, we will reason not only about the functional correctness of code, but also the space, time, and other resources used in a computation.  The relatively simple evaluation model of SML makes it easy to do this.

Office and Consulting Hours

The TAs have regular office hours during the day, consultants have evening consulting hours.  Office hours are shown in the above table. 

Course Materials

There is no official textbook for the course.  However, there are some useful resources:

The following textbooks are excellent references and are on reserve in the Engineering library:

• ML for the Working Programmer, L. C. Paulson, 2nd ed., Cambridge Univ. Press, 2000.  ISBN 0 521 56543 X
• Elements of ML Programming, ML97 Edition, Jeffrey D. Ullman, Prentice Hall, 1998.  ISBN 0 13 790387 1
• Program Development in Java: Abstraction, Specification, and Object-Oriented Design. Barbara Liskov, John Guttag. Addison-Wesley, 2001. ISBN  0-201-65678-6.

Two convenient online sources that we will be using from time to time are:

• Programming in Standard ML, Robert Harper
• Notes on Programming in SML/NJ, Riccardo Pucella

In addition, there are many other resources on the Web for Standard ML, including tutorials, free compilers, libraries, etc.

We will be using the Standard ML of New Jersey (SML/NJ version 110) compiler, interactive system, libraries, and tools for all examples and homework.  SML/NJ is a freely available, open source development system brought to you from Lucent's Bell Labs -- the same place that developed C and Unix.   SML/NJ runs under Win32 systems and just about any flavor of Unix.   Sadly, there is no support for the Macintosh.  There are other SML compilers freely available, such as MoscowML which do run on the Macintosh.  However,  your code will be tested using automated scripts that assume SML/NJ, so your programs must correctly run under SML/NJ.

Course Requirements

Students are responsible for all material in the assigned readings, as well as material covered in lectures and in recitations. There will be six problem sets, two preliminary exams, and a final project presentation.  Each problem set will involve a programming assignment and may include written exercises.  Exams will cover material presented in class and will require you to do some heavy thinking on your feet.  Filling the course evaluations will count for 1% of the final grade.

Assignments are due at 11:59pm on the due date. However, assignments will be accepted up to 48 hours late, but at a 10% penalty if late up to 24 hours, and a 20% penalty if late up to 48 hours. We can't accept later assignments because it interferes with grading. Assignments are submitted online.  You should try to get started on assignments early. The best use of your time and the machine's time is to think about the problems before typing anything at the computer. (Again: think before typing.)

Karma problems. Assignments may include optional problems called karma problems. These problems exist to provide extra challenge to those who want it. Karma problems will be graded, and but doing these problems mostly just gives you good karma. In some cases it can increase your score on the assignment, but usually it will not. Students who do karma problems will be noticed and doing them may be taken into account when assigning the final grade. However, spending your time on regular problems is almost always a more effective way to improve your overall score. Tackle karma problems only after you're sure you have the rest of the assignment well in hand.

Makeup exams must be scheduled within two weeks of the start of class.  Check now to see if you have a conflict with another class and contact Professor Myers immediately to reschedule.

Joint Work

Some assignments will be done individually. Others (including the projects) will be done in pairs. For assignments done in pairs you will submit a single joint assignment with both names on it.

Under no circumstances may you hand in work done with (or by) someone else under your own name. If you have a question, consult the course staff.  Your code should never be shared with anyone other than your partner. You would be amazed at how easy it is to tell when people have worked together on problem sets, so please don't make life unpleasant for all of us by breaking these rules. The penalties for cheating at Cornell are severe, and can include expulsion; see the CS Department's Code of Academic Integrity. If you are unsure about anything, please ask.

Public Lab Facilities

CIT and various colleges on campus provide public Macintosh and PC facilities. You may use your own machine or public ones. For your convenience, F# is installed on the Windows machines in Upson B7. If you are interested in installing OCaml on your own machine, then see the course software page for details. Students in this course also have access to the CSUGLab.