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’s 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’s 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 027
• Class Time: MW 2:00-2:50
• Lab Time: F 2:00-4:50
• Class Location: S 025
• Textbook: Data Structures and Program Design Using Java: A Self-Teaching Introduction by Dheeraj Malhotra, Neha Malhotra. ISBN: 9781683924647. Free with student membership in ACM via Skill Soft Library
• Additional resources: (All free with ACM student membership from Skill Soft)
  • Handbook of Data Structures and Applications, Second Edition
  • Data Structures and the Java Collections Framework, Third Edition
  • Courses starting with "Data Structures & Algorithms in Java"
  • Courses starting with "Advanced Data Structures & Algorithms in Java"
• Additional Resources from O'Reilly (also free with ACM Student membership)
  • Beginning Java Data Structures and Algorithms
  • Video: From 0 to 1: Data Structures & Algorithms in Java
• Foundational work in Data Structures: (from O'Reilly)
  • Art of Computer Programming, The: Volume 1: Fundamental Algorithms
  • Art of Computer Programming, Volume 2: Seminumerical Algorithms, 3rd Edition
  • Art of Computer Programming, The: Volume 3: Sorting and Searching
  • Art of Computer Programming, Volume 4A, The: Combinatorial Algorithms, Part 1

Course Content

Policies

• Integrity
• Late work
• Software Standards
• Software Development Report: A sample software development report: File:SDRDemo1.pdf|thumb|A sample Software Development Report

Assignments

• Reviewing programming and Java
• Turing Machine

Grades

• 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	Wednesday	Friday: Lab
8/16:	8/18:	8/20: Lab 1 Review of Java Code
8 23: Chapter 1 Syllabus & Intro to Data Structures	8/25: Chapters 1 & 4 Intro to Data Structures & Java	8/27: Lab 2 Turing Machine Design
8/30: Chapters 2 & 3 Arrays & Linked Lists	9/1: Chapter 5 Queues	9/3: Lab 3 Turing Machine Code
9/6: Chapter 5 Queues	9/8: Chapter 7 Stacks	9/10: Lab 4 Stack and Queue Design
9/13: Chapter 7 Stacks	9/15: Exam 1	9/17: Lab 5 Stack and Queue Code
9/20: Chapter 8 Trees	9/22: Chapter 8 Trees	9/24: Lab 6 Tree Design
9/27: Chapters 8 & 9 Trees	9/29: Chapter 9 Search Trees	10/1: CCSC:MW
10/4: Review	10/6: Exam 2	10/8: Fall Break
10/11: Chapter 6: Searching & Sorting	10/13: Chapter 6 Searching & Sorting	10/15: Lab 7: Tree Code
10/18: Chapter 11 Files	10/20: Adv Sorts and Searches	10/22: Lab 8: Sort/Search Design
10/25: Adv Sorts & Searches	10/27: Secure Programming	10/29: Lab 9: Sort/Search Code
11/1: Exam 3	11/3: Chapter 12 Graphs	11/5: Lab 10: Graph Design
11/8: Chapter 12 Graphs	11/10: Chapter 10 Hashing	11/12: Lab 11: Graph Code
11/15: Chapter 10 Hashing	11/17: Exam 4	11/19: Lab 12: Hash, etc. Design
11/22: Advanced Data Structures	11/24: Thanksgiving Break	11/26: Thanksgiving Break
11/29: Current Topic	12/1: Review	12/3: Lab 13: Hash, etc. Code
12/6: Final Exam week	12/8: Final Exam: 1:00-2:50	12/10:

Services

ADA Statement for Syllabi: 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@betheluniversityadmin.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.