Syllabus and general information for MCS-177: Introduction to Computer Science I (Fall 1999)

Overview

The central theme of this course is the activity of abstraction, which is ignoring irrelevant specifics. The quest for generality will motivate our study of programming: you will learn how to express general procedural ideas and how to use general categories of data in terms of their operational properties.

We will also use abstraction to make computational processes easier to think about. You will learn the relationship between the form of a procedure and that of the computational process it generates, including the resource consumption of that process. Also, you will learn how to prove that a procedure has the desired effect, and why such proofs are not always possible.

Prerequisites

Although there are no formal prerequisites, you should understand the material that is typically covered in high school algebra.

Office hours

I will be available in my office (OHS 303) 11:30-12:20 Tuesdays, 2:30-3:20 Wednesdays, 9:00-9:50 Thursdays, 1:30-2:20 Fridays, and by appointment. Or try your luck: just stop by and see whether my door is open. You may send me electronic mail at max@gustavus.edu or call me at extension 7466. I'll try to put any updates to my office hours on my web page, so check there if in doubt.

World Wide Web

All course materials will be available through my World Wide Web page. The URL for this course is http://www.gustavus.edu/~mc27/. After this syllabus I will give hardcopy handouts only to those students who want them.

Textbook

The textbook for the course will be Hailperin, Kaiser, and Knight's Concrete Abstractions: An Introduction to Computer Science Using Scheme, Brooks/Cole Publishing Co., 1999.

Tests

There will be two intra-term tests and a final exam, as shown on the syllabus below. (Note that the final exam will be as scheduled by the registrar. The date and time shown in the syllabus are the tentative projection from the registrar's office, but are subject to change by that office.)

Exams will be closed-book and mostly closed-notes. You may, however, use a single 8 1/2 by 11 sheet of paper with hand-written notes for reference. (Both sides of the sheet are OK.)

Honor

Students are encouraged to discuss the course, including issues raised by the assignments. However, the solutions to assignments should be individual original work unless otherwise specified. If an assignment makes you realize you don't understand the material, ask a fellow student a question designed to improve your understanding, not one designed to get the assignment done. To do otherwise is to cheat yourself out of understanding, as well as to be intolerably dishonorable.

Any substantive contribution to your solution by another person or taken from a publication should be properly acknowledged in writing. Failure to do so is plagiarism and will necessitate disciplinary action.

The same standards regarding plagiarism apply to team projects as to the work of individuals, except that the author is now the entire team rather than an individual. Anything taken from a source outside the team should be be properly cited.

One additional issue that arises from the team authorship of project reports is that all team members must stand behind all reports bearing their names. All team members have quality assurance responsibility for the entire project. If there is irreconcilable disagreement within the team it is necessary to indicate as much in the reports; this can be in the form of a ``minority opinion'' or ``dissenting opinion'' section where appropriate.

Late assignments

All homework and lab assignments are due at the beginning of class on the day indicated. Late assignments will be penalized by one ``grade notch'' (such as A to A- or A- to B+) for each weekday late or fraction thereof. However, no late assignments will be accepted after graded assignments are handed back.

If you are too sick to complete an assignment on time, you will not be penalized. Simply write ``late due to illness'' at the top of the assignment, sign your name and hand it in. Other circumstances will be evaluated on a case-by-case basis.

Grade changes

Please point out any arithmetic or clerical error I make in grading (or one made by a lab instructor), and I will gladly fix it. You may also request reconsideration if one of us has been especially unjust.

Grading

I will provide you with a grade on each homework and lab assignment, and on each test, in addition to the mid-term and final grades, so that you may keep track of your performance. As a guideline, the course components will contribute to your final grade in the proportions indicated below:

Style guidelines

All homework and lab reports should be readily readable, and should not presuppose that we already know what you are trying to say. Use full English sentences where appropriate (namely almost everywhere) and clear graphs, tables, programs, etc. Remember that your goal is to communicate clearly, and that the appearance of these technical items plays a role in this communication process. Be sure your assignments are always stapled together and that your name is always on them.

For a more detailed set of guidelines, refer to Suggestions for clear lab reports in computer science courses reports. I recommend that you look at this document and, if you have questions about lab write-ups, ask!

Accessibility

Please contact me immediately if you have a learning or physical disability requiring accommodation.

Syllabus

This is my best guess as to the rate at which we will cover material. However, don't be shocked if I have to pass out one or more revised syllabi.
DateReadingTopicDue
9/81.1-1.2Introduction; simple expressions
9/9Lab 0: An ungraded introduction
9/101.2-1.3Compound procedures; conditionals

9/132.1Recursion
9/14Lab 1: Quilting
9/152.2InductionHomework #1
9/16Lab 1 (continued)
9/172.3-2.4Further examples & custom-sized quilts

9/203.1Iteration
9/21Lab 1 (continued)
9/223.2Using invariantsHomework #2
9/23Lab 1 (concluded)
9/243.3Perfect numbers, internal definitions, & let

9/273.4Iterative improvementLab #1
9/28Lab 1.5: Empirical Time Tests (ungraded)
9/29Review/catch-up
9/30Test #1, 7:00-8:30 PM (no lab)
10/13.5The Josephus Problem

10/44.1Orders of growth
10/5Nobel Conference (no class)
10/6Nobel Conference (no class)
10/7Lab 2: Orders of Growth
10/84.2Tree recursion and digital signaturesHomework #3

10/11More on tree recursion and digital signatures
10/12Lab 2 (continued)
10/135.1Procedural parametersHomework #4
10/14Lab 2 (concludes)
10/155.2Uncomputability

10/185.3Procedures that return proceduresLab #2
10/19Lab 3: Fractal Curves
10/205.4Application of higher-order programming
10/21Lab 3 (continued)
10/22Reading break (no class)

10/25Reading break (no class)
10/26Lab 3 (continued)
10/276.1-6.2Data abstractionHomework #5
10/28Lab 3 (concludes)
10/296.3Representations and implementations

11/16.4Three-pile NimLab #3
11/2Lab 4: Nim with Strategies
11/37.1-7.2Lists
11/4Lab 4 (continued)
11/57.3Basic list processingHomework #6

11/8Review/catch-up
11/9Test 2, 7:00-8:30 PM (no lab)
11/107.4Iterative list processing
11/11Lab 4 (concludes)
11/127.5Tree recursion and lists

11/157.6Movie query systemLab #4
11/16Lab 5: Movie Query System
11/178.1Binary search trees
11/18Lab 5 (continued)
11/198.2Efficiency issues with binary search trees

11/228.3Expression trees
11/23Lab 5 (continued)
11/24Catch-upHomework #7
11/25Thanksgiving Break (no class)
11/26Thanksgiving Break (no class)

11/299.1-9.2Generic operations: multiple representations
11/30Lab 5 (concludes)
12/19.2 & 9.4More on multiple representations; computer graphicsLab #5
12/2Lab 6: Implementing Computer Graphics
12/3More on computer graphics

12/69.3Exploiting commonality
12/7Lab 6 (continued)
12/8Special topic (or catch-up)Homework #8
12/9Lab 6 (concludes)
12/10Review/evaluationLab #6

12/14Final exam, 1:00-3:00 PM (tentative)


Course web site: http://www.gustavus.edu/~mc27/
Instructor: Max Hailperin <max@gustavus.edu>