CSC 122: Programming 2: Data Structures: 3 hours.

Description

A continuation of Programming 1. Students learn data structures including stacks, queues, trees, lists, graphs. Other data structures and sorting and searching are covered. Students learn both how to use the data structures via standard api's and how to implement them. 2 lectures and one lab per week. Lab: CSC 122. Prerequisite: CSC 121

Goals for CSC 122 are:

1. Enhance the ability to program
2. Understand different data structures
3. Be able to use different data structures well

Course outcomes for CSC 122 are:

• Upon completion of CSC 122, students will know:
  • how to use and build different data structures including stacks, queues, trees, graphs, and lists
  • a number of different searches and sorts (including O(nlogn) sorts)
  • how to identify Big-O for given algorithms
  • how to completely document code and programs
  • how to thoroughly test a program (including most error conditions)
  • how to identify some potential security issues with code being developed
  • the importance of designing before coding and practice it when warranted.

Program outcomes for CSC 122 are:

1. Analyze a complex computing problem and to apply principles of computing and other relevant disciplines to identify solutions. (Computing student learning outcome 1)
2. Design, implement, and evaluate a computing-based solution to meet a given set of computing requirements in the context of the program\x92s discipline. (Computing student learning outcome 2)
3. Communicate effectively in a variety of professional contexts. (Computing student learning outcome 3)
4. Recognize professional responsibilities and make informed judgments in computing practice based on legal, ethical, and moral principles. (Computing student learning outcome 4)
5. Function effectively as a member or leader of a team engaged in activities appropriate to the program\x92s discipline. (Computing student learning outcome 5)
6. Learn new areas of technology. (Computing student learning outcome 6)

Integration

1. Self-learning at the introductory level by having some programming assignments that include using some simple features not covered in class (such as using a pre-defined data type)
2. Note taking at the introductory level by not posting lecture notes and holding students responsible for the content.
3. Technical writing at the application level by requiring students to do a formal software development report and requiring quality writing (and grading the quality of the writing), Also by the end of the semester by refusing to accept reports that don't meet a bare min. standard (such as standards, spell check, using bullet lists as appropriate.
4. Team work at the introductory level by having at least two assignments where students are working in pairs with one developing the data structure and the other using it. Students need to take on both roles during the semester. Students also might have a third assignment where they are assigned one of the two roles and they have a partner that they don't know and must only communicate via the interface.
5. Professionalism at the introductory level by having students track how long it takes to write programs (so that they are better equip to estimate this in the future) and comment on what they learned and what they would want to to better with a program if they could.
6. Cybersecurity at an introductory level by requiring students to document possible invalid input what happens for all programs. By the end of the semester, they should handle some of the invalid input (i.e. secure programming).
7. Ethics at an introductory level by having at least one program assigned that could have ethical implications and having the students discuss that in their reports.

Details

• Professor: Dr. Cathy Bareiss
• Office SB 31
• Class Time:
• Class Location:
• Textbook: Data Structures and Program Design Using Java: A Self-Teaching Introduction, Dheeraj Malhotra, Neha Malhotra

Course Content

Policies

• Integrity
• LatePolicy

Programs

1. Finite State Machine
2. Nondeterministic Finite State Machine
3. A game with stacks and queues
4. Sorting: Internal vs. external
5. Hashing
6. Using a binary tree to do Huffman codes
7. Own data structure
8. Coloring Graphs

Homework, Assignments, Quizzes, etc.

1. Reactions to current events/publications. A reaction to an article includes enough to convince me that you have read the entire article and not just the headline or first paragraph. It should include s summary of what was said and your reaction. Be sure to give a complete reference to the item. These should be turned in as a hard copy in class within one week of the item being published. You may pick when. Each one does have a deadline. These must be unique to this course.
   1. Write a reaction to one article in the ACM TechNews. This needs to be completed by midterm.
   2. Write a reaction to one article in XRDS. This needs to be completed before the final.
   3. Write a reaction to one article in the Communication of the ACM. This needs to be completed before the final
2. Other assignments or quizzes as assigned.

Extra credit

To be eligible for extra credit you must be attending class 80% of the time (according to when you turn it in). If you are in sports that causes you to miss class, you should not be missing class on any of the other days.

There are three types of extra credit available:

1. Extra credit for an assignment or exam. This will be if I determine to offer the entire class some credit for improving work on a given item. This will be used to raise the grade on that item. Details will be given in class when/if this happens.
2. The College Gems. This can have a direct impact on your grade. See that page for more details
3. Extra credit that will be used at the end of the class to decide if I should "bump" you up to the next mark.
   1. There may be events that I give extra credit for attending. To earn this, you must attend the event (in person unless otherwise stated) and write a 1/2 page summary of what was said. This is to be turned in as a hard copy within 3 working days of the event.
   2. Do a second reaction to an article in the Communications of the ACM
   3. Do a second reaction to an article in the ACM TechNews.

Grades

Your grade is made up of:

1. Exams (50%) with the final exam being worth twice a normal exam
2. Programs (45%)
3. Homework, quizzes, etc. (5%)

• Grade scale
  • 93% <= average <= 100% → A
  • 90% <= average < 93% → A-
  • 87% <= average < 90% → B+
  • 83% <= average < 87% → B
  • 80% <= average < 83% → B-
  • 77% <= average < 80% → C+
  • 73% <= average < 77% → C
  • 70% <= average < 73% → C-
  • 67% <= average < 70% → D+
  • 63% <= average < 67% → D
  • 60% <= average < 63% → D-
  • 0% <= average < 60% → F

Tentative Schedule

Monday Lab	Wednesday	Thursday Lab	Friday
Aug 15	Aug 17	Aug 18: Lab 1 FSM	Aug 17 Chapter 1
Aug 22 Lab 1 cont.	Aug 24 Chapters 2 & 4	Aug 25: Lab 2 NFSM	Aug 26: Chapters 2 & 4
Aug 29 Lab 2 cont.	Aug 31 Chapter 7	Sep 1 Stack/Queue Design	Sep 2 Chapter 7
Sep 5: Labor Day	Sep 7 Chapter 5	Sep 8 SQ Design cont.	Sep 9 Chapter 5
Sep 12 SQ Build	Sep 14 more stacks and queues	Sep 15 SQ Build cont.	Sep 16 Exam 1
Sep 19 Sorts Design	Sep 21 Chapter 6	Sep 22 Sorts Design cont.	Sep 23 Chapter 6
Sep 26 Sorts Build	Sep 28 Chapter 10	Sep 29 Sorts Build cont.	Sep 30 Chapter 10
Oct. 3 Hashing Design	Oct 5 Chapter 8	Oct 6: Fall Break	Oct 7: Fall Break
Oct 10 Hashing D cont.	Oct 12 Chapter 8	Oct 13 Hashing Build	Oct 14 Chapter 8
Oct 17 Hashing B cont.	Oct 19 Review of Sorts	Oct 20 Tree Design	Oct 21 Exam 2
Oct 24 Tree D cont.	Oct 26 Chapter 8	Oct 27 Tree Build	Oct 28 Chapter 8
Oct 31 Tree B cont.	Nov 2 Chapters 8 & 9	Nov 3 Own Design	Nov 4: Chapter 9
Nov 7 Own D cont.	Nov 9 Advanced data structures	Nov 10: CCSC:SE Own Build	Nov 11: CCSC SE Exam 3
Nov 14 Own B cont.	Nov 16 Chapter 12	Nov 17 Graph Design	Nov 18 Chapter 12
Nov 21 Graph D cont.	Nov 23 Thanksgiving break	Nov 24: Thanksgiving break	Nov 25: Thanksgiving break
Nov 28 Graph Build	Nov 30 Exam 4	Dec 1 Graph B cont.	Dec 2: Review
Dec 5 Finals	Dec 7: Finals Final: 3:30pm	Dec 8: Finals	Dec 9:Finals

Campus Integrity Policy

The student handbook (p. 156) states: “Any act of deceit, falsehood or stealing by unethically copying or using someone else’s work in an academic situation is strictly prohibited.

1. A student found guilty of plagiarism or cheating will receive an “F”(zero) for that particular paper, assignment or exam. Should this occur, the professor will have an interview with the student and will submit a written report of the incident to the academic dean.
2. If a second offense should occur, the student will be asked to appear before the professor, the academic dean and the vice president for student development.
   
   

The student should realize that at this point continuation in a course and even his/her academic career may be in jeopardy. In the event of a recommendation for dismissal, the matter shall be referred to the Student Development Committee.”

Covid Policy

Everyone should follow the current Bethel University covid policy. See: https://www.betheluniversity.edu/intheknow for details

Services

The Americans with Disabilities Act (ADA) is a law which provides civil rights protection for people with disabilities. Bethel University, in compliance with equal access laws, requests that students with disabilities seeking to acquire accommodations make an appointment with the Center for Academic Success—Disability Services. It is located in the Miller-Moore Academic Center, 033. You may also phone 574-807-7460 or email rachel.kennedy@betheluniversity.com.edu for an appointment.

DEI Statement

During this particularly difficult time, this statement momentarily underscores and deepens what is expressed in the Lifestyle Covenant regarding the dignity of all humans. The statement will remain in all Bethel Faculty syllabi until spring 2023 and then be remanded back to the Faculty. Bethel University respects the dignity of all God’s image-bearers, and stands against racism, prejudice, and discrimination. Because Christ calls us to love our neighbor as ourselves, Christian discipleship includes pursuing the good of those who suffer injustice due to their color, race, or ethnicity. Therefore, we aim to continually transform our classrooms into safe and hospitable spaces where we listen to one another with mercy, learn from and value each other with tenacity, and commit to pursuing justice for the most vulnerable in our community.

Education Majors:

Please use the link below to review all appropriate standards. Standards