Course Information

Section 2: MWF 11:30–12:20, Sci Cntr 256
Professor: Jeff Knerr
Office: Sci Cntr 238A (at back of 240 and 238)
Office hours: I will definitely try to be around on Mondays from 2-4pm. You can also stop by whenever my door is open. I usually work from home on Thursdays.

Other Sections:

• David Mauskop (MWF 9:30–10:20)
• Tia Newhall (TR 11:20–12:35)

Welcome to CS21. This course will introduce fundamental ideas in computer science while also teaching you how to write computer programs. We will study algorithms for solving problems and implement solutions in the Python programming language. Python is an interpreted language that is known for its ease of use. We also introduce object-oriented programming and data structures. A deeper coverage of these topics will be presented in CS 35.

This course is appropriate for all students who want to learn how to write computer programs and think like computer scientists. It is the usual first course for computer science majors and minors. Students with advanced placement credit or extensive programming experience should place out of this course and instead begin with CS31 or CS35.

Textbook:

We will primarily be using the online book How to think like a computer scientist: Learning with Python by Elkner, Downey and Meyers.

See the Schedule for each week's reading assignment.

Here are a few other useful online resources:

• Basic Unix Commands
• vim basics
• Python Tutor
• The Python tutorial
• Python documentation (Note: we are using v2.7)

Goals for the course:

By the end of the course, we hope that you will have developed the following skills:

• Given a program, be able to simulate on paper how a computer would execute the program, and show the results that would be produced.
• Given a problem, be able to design a clear, concise, and correct pseudocode algorithm to solve it.
• Given a pseudocode algorithm, be able to successfully implement it in Python.
• Be able to use top-down design to sub-divide a large problem into reasonably-sized modular sub-problems.
• Given several algorithms for solving the same problem, be able to analyze which algorithm would be more efficient in terms of running time.
• Develop debugging and unit testing skills. Consistently use these skills while implementing programs.

Schedule

This is a tentative schedule; it may change as we go.

WEEK	DAY	ANNOUNCEMENTS	TOPIC & READING	LABS
1	Jan 16	MLK Day...no classes	Introduction to Python and Unix python and unix data types variables, assignment calling built-in functions print(), type(), int(), float(), str() user input: raw_input() writing and running a program for loops, sequences, range() Ch 1: The way of the program Ch 2: Variables, expressions and statements Ch 4, Sec 9: keyboard input Ch 4, Sec 10: type conversion Ch 2b: lists, looping, range()	In class topics: lecture 0 variables for loops Lab 0: unix, editing
	Jan 18
	Jan 20
2	Jan 23		Writing simple programs def main() more for loops accumulator pattern strings and lists: mutable vs immutable indexing, slicing, len() print(), print formatting from math import * Ch 2: Variables, expressions and statements Ch 2b: lists, looping, range() Ch 7: Strings (sections 1-4, 6, 13 only) Ch 9: Lists (sections 1-3, 5, 6, 8)	In class topics: slicing,indexing string formatting accumulator Lab 1: first progs
	Jan 25
	Jan 27
3	Jan 30	Drop/add ends	Conditionals boolean type comparison operators (<, >, ==, !=, etc) logical operators (and, or, not) mod operator if/elif/else nesting the in operator string comparisons Ch 4: Conditionals (skip sections 8,11) Ch 7: Strings (in operator)	In class topics: branching and, or, not vim tips Lab 2: numbers and strings
	Feb 01	Q1 Study Guide
	Feb 03	Quiz 1
4	Feb 06		First functions, while loops writing simple functions arguments, parameters stack diagrams while loops random numbers Ch 3: Functions (just 3.1 - 3.3) Ch 5: Fruitful functions (just 5.1, 5.2) Ch 6: Iteration	In class topics: while loops functions Lab 3: branching
	Feb 08
	Feb 10
5	Feb 13		Graphics, Using Objects intro to objects intro to graphics RGB colors object.method() more practice with functions mouse and keyboard input animation Notes on the Zelle graphics library Zelle's Chapter 5: Objects and graphics Zelle Graphics Module	In class topics: graphics Lab 4: rock-paper-scissors
	Feb 15	Q2 Study Guide
	Feb 17	Quiz 2
6	Feb 20		Fruitful Functions more practice with functions incremental development boolean functions stack diagrams passing lists to functions exceptions (try/except) Ch 3: Functions Ch 5: Fruitful functions Stack diagrams handout A Better/Longer Stack Diagram Example Ch 11, Sec 7: exceptions	In class: more functions Lab 5: graphics
	Feb 22
	Feb 24
7	Feb 27		File IO, Top-Down Design reading/writing files top-down design function stubs list-of-lists string and list methods Ch 10, Sec 8: Text Files Intro and CompSci sections from Wikipedia TDD Ch 10, Sec 6: str, list methods	In class: file i/o,top-down design Lab 6: bugs
	Mar 01	Q3 Study Guide
	Mar 03	Quiz 3
	Mar 06	Spring Break
	Mar 08
	Mar 10
8	Mar 13		More TDD reading/writing files top-down design function stubs list-of-lists string and list methods Ch 10, Sec 8: Text Files Intro and CompSci sections from Wikipedia TDD Ch 10, Sec 6: str, list methods	In class: file i/o, top-down design Lab 07: cryptoq design
	Mar 15
	Mar 17
9	Mar 20		Searching linear search analysis of algorithms binary search Binary Search (skip the recursive version) Ben's musicAlgo videos	In class: searching Lab 07: cryptoq
	Mar 22	Q4 Study Guide
	Mar 24	CR/NC/W Deadline Quiz 4
10	Mar 27		Sorting selection sort analysis of algorithms insertion and bubble sort idea of merge sort, recursion Ben's musicAlgo selection sort video interactivepython selection sort interactivepython bubble sort	In class: sorting Lab 8: climate data
	Mar 29
	Mar 31
11	Apr 03		Recursion recursive call base case leap of faith... graphics examples back to merge sort Ch 11: Recursion (Skip tuples) Recursion (from Wikipedia) PYTHON TUTOR	In class: recursion Lab 9: sorting
	Apr 05	Q5 Study Guide
	Apr 07	Quiz 5
12	Apr 10		Classes and Objects creating our own objects instance variables self, __init__, __str__ methods getters/setters class writer vs class user interface/information hiding Ch 13: Classes and objects Ch 14: Classes and functions Ch 15: Classes and methods	In class: classes and objects Lab 10: recursion
	Apr 12
	Apr 14
13	Apr 17		Classes and Objects more examples	In class: classes and objects Lab 11: bug graphics
	Apr 19
	Apr 21	Q6 Study Guide
14	Apr 24	Quiz 6	Linked Lists python list vs linked list Node() class LinkedList() class linked list methods analysis of algorithms Ch 18: Linked Lists	In class: linked lists Lab 12: linked lists
	Apr 26
	Apr 28	Final Topics
	May 06	Final Exam: Sat, May 6, 7-10pm, Sci Cen 101

Grading Policies

Grades will be weighted as follows:

35%	Lab assignments
30%	Quizzes
30%	Final Exam
5%	Class Participation

Exam and Quizzes

Quizzes will be given at the beginning of class on the days posted on the Schedule. Please look over these dates carefully and contact the professor in advance if you cannot be in class for a quiz.

If you are not present on the day of a quiz, and do not let me know ahead of time that you are missing class, you will receive a zero for that quiz.

There will be one final exam for the semester. Details and dates will be released during the semester. Please read the section on accommodations if you are in need of extra time. You must inform me of accommodations or conflicts at least 2 weeks in advance of the exam.

Lab Policy

This course features weekly lab assignments which are the largest component of your course grade. Lab attendance is required by all students, unless you have already completed and submitted the lab assignment for the week. You must attend the lab session for which you are enrolled:

Weekly Lab Sessions
CS21 A 1:05—2:35pm Tuesdays	Knerr	Science Center 240
CS21 B 2:45—4:15pm Tuesdays	Newhall	Science Center 240
CS21 C 1:15—2:45pm Wednesdays	Mauskop	Science Center 240
CS21 D 3:00—4:30pm Wednesdays	Mauskop	Science Center 240

Lab assignments will typically be assigned in class at the beginning of the week and will be due before midnight on Saturdays. You are strongly encouraged to start early and to attend the study sessions for extra practice.

You will submit you assignments electronically using the handin21 program. You may submit your assignment multiple times, and a history of previous submission will be saved. You are encouraged to submit your work regularly.

Late Policy:

Late assignments are not accepted and will receive zero credit (see exceptions below). Even if you do not fully complete an assignment, you should submit what you have done to receive partial credit.

The CS labs are open 24 hours a day, 7 days a week for you to use for CS21 lab assignments.

If you feel that you need an extension on an assignment or that you are unable to attend class for two or more meetings due to a medical condition (e.g., extended illness, concussion, hospitalization) or other emergency, you must contact the dean's office and your instructors. Faculty will coordinate with the deans to determine and provide the appropriate accommodations. Note that for illnesses, the College's medical excuse policy, states that you must be seen and diagnosed by the Worth Health Center if you would like them to contact your class dean with corroborating medical information.

Academic Integrity

Academic honesty is required in all your work. Under no circumstances may you hand in work done with (or by) someone else under your own name. Your code should never be shared with anyone; you may not examine or use code belonging to someone else, nor may you let anyone else look at or make a copy of your code. This includes, but is not limited to, obtaining solutions from students who previously took the course or code that can be found online. You may not share solutions after the due date of the assignment.

Discussing ideas and approaches to problems with others on a general level is fine (in fact, we encourage you to discuss general strategies with each other), but you should never read anyone else's code or let anyone else read your code. All code you submit must be your own with the following permissible exceptions: code distributed in class, and code found in the course text book. In these cases, you should always include detailed comments that indicates on which parts of the assignment you received help, and what your sources were.

Failure to abide by these rules constitutes academic dishonesty and will lead to a hearing of the College Judiciary Committee. According to the Faculty Handbook: "Because plagiarism is considered to be so serious a transgression, it is the opinion of the faculty that for the first offense, failure in the course and, as appropriate, suspension for a semester or deprivation of the degree in that year is suitable; for a second offense, the penalty should normally be expulsion." Be aware that we will be routinely running plagiarism detection software on the lab solutions of students from all sections of CS21.

Please contact me if you have any questions about what is permissible in this course.

Student Support

Lauri Courtenay is the CS Department's Academic Support Coordinator. She will be working closely with our student mentors, also known as Ninjas, to help you learn how to program and think like a computer scientist. The CS21 Ninjas will assist me in class and run evening study sessions in the birds' nest (Sci 256). The CS21 Ninjas (student mentors) are: Annie Zhao, Colin Pillsbury, Carlo Sivilotti, Jeffrey Novak, Nhung Hoang, Rye Buckley, Kyra Moed, Kei Imada, Zoe Kyaw, and Katherine Huang.

Study Sessions

You are invited -- and encouraged -- to participate in Ninja evening study sessions to prepare for quizzes, to discuss programming concepts, and to get friendly assistance in working on lab assignments. Our CS mentoring team is dedicated to helping students, who have no prior knowledge of computer science, learn to program in Python while keeping their senses of humor intact. As an added bonus, free snacks will be provided at the sessions. The sessions are held:

Weekly Evening Ninja Sessions
Tuesdays	7—9pm	Sci Center 256
Wednesdays	7—10pm	Sci Center 256
Fridays	7—9pm	Sci Center 256

Accessing the CS labs after hours

You can use your ID to gain access to the computer labs at nights and on the weekends. Just wave your ID over the microprox reader next to the lab doors. When the green light goes on, just push the door to get in (the door knob will not turn). If the green light doesn't go on, then we need to enter your microprox number into the system. Email local-staff@cs.swarthmore.edu (or see Bridget) if you have problems with this. If the building is locked, you can use your ID to enter the door between Martin and Cornell library. For this class, your ID will give you access to the labs in rooms 238, 240, and 256 and Clothier 16.

Academic Accommodations

If you believe that you need accommodations for a disability, please contact Leslie Hempling in the Office of Student Disability Services (Parrish 113) or email lhempli1 to arrange an appointment to discuss your needs. As appropriate, she will issue students with documented disabilities a formal Accommodations Letter. Since accommodations require early planning and are not retroactive, please contact her as soon as possible. For details about the accommodations process, visit the Student Disability Service website.

To receive an accommodation for a course activity, you must have an Accommodation Authorization letter from Leslie Hempling and you need to meet with me to work out the details of your accommodation at least one week prior to the activity.

You are also welcome to contact me privately to discuss your academic needs. However, all disability-related accommodations must be arranged through Leslie Hempling in the Office Of Student Disability Services.

How to Succeed in CS 21

• Attend class.
  The primary introduction to course material is through class lecture. Additionally, we often do lab exercises during class. This is an important part of the learning process, as these exercises give you immediate experience with the material we are covering.
• Read the material before you come to class.
  Don't worry about total comprehension, but at least get a feel for what we will be covering that week. If you have some understanding of the material coming into class, it will be easier for you to ask questions during class, rather than later when help may not be available.
• Ask questions if you don't understand.
  This means both during class and while doing lab assignments. This class continually builds on previous material, so if you don't understand something one week, it will continue to be a problem the next week, and the week after that, and so on. If you need help, ask your classmates (make sure you have read the "Academic Integrity" section below first), attend study sessions, come talk with me during my office hours, or email me your question.
• Start the lab assignments early.
  I realize this one is not always easy to do, but if you can get in the habit of doing this, you will be much better off. If you get stuck early (i.e., not two hours before it is due), there will be time to look for help. In addition, if you start early enough, you can take a break, go do something else, and come back later. I find I always have at least a few new ideas when I come back to a problem after a break. If you wait until the last minute, you can't do this.
• Practice, practice, practice.
  The only effective way to learn the material and pass the quizzes and exams is to consistently do the labs. Finish all of the assigned programs (and do some extras, for fun!). Even if you don't get them done on time, they will still help you learn the material.
• Seek help early and often.
  Because course material builds on previous material, it is essential to your success in this class that you keep up with the course material. If you are having difficulty with a programming assignment, if you didn't follow something covered in lecture, if you feel you need some extra help understanding or practicing some of the course material, or if you just want to discuss something from a lecture, an assignment, or the text, please come to my office hours.
• Attend CS21 Labs and Study Sessions.
  Lab attendance is required. The student Ninjas hold evening study sessions each week. You are encouraged to participate in these sessions. The Ninjas will help you prepare for quizzes, will provide additional instruction in programming concepts, and will provide friendly assistance on your lab assignments.

Programming Style

Programming is not a dry mechanical process, but a form of art. Well written code has an aesthetic appeal while poor form can make other programmers and instructors cringe. Programming assignments will be graded based on style and correctness. Good programming practices usually include many of the following principles:

• A comment at the top of the program that includes
  • Program authors
  • Date or Dates
  • A brief description of what the program does
• Concise comments that summarize major sections of your code
• Meaningful variable and function names
• Function comments that include:
  1. description of what function does
  2. description of input value(s) (parameter values)
  3. description of return value
• Well organized code
• White space or comments to improve legibility
• Avoidance of large blocks of copy-pasted code

Also, look over the Python Code Style Guide for more details and some examples of good code style.

Useful Links

Links that are related to the course may be posted here. If you have suggestions for links, let me know.

pythonchallenge
Algorithms to Live By...
How To Think Like a Computer Scientist: Python for Software Design
Python Tutor
Vi Quick Reference
Python style guide From Prof. Tia Newhall
Using Unix
Basic Unix Commands
Graphics reference
Dive Into Python
(A Semi-Official) Python FAQ Zone
NodeBox
Python Documentation (Note: we are using v2.7)
emacs beginner's guide

Last updated: Tuesday, September 22, 2020 at 12:25:33 PM