Lectures will take place in Tate Hall B50. Labs will take place in Keller Hall 1-250. Lectures and labs can also be attended remotely on Zoom.
Office hours will start from the second week of the course. TAs' office hours are individual. Office hours labeled with (P) will be in person in the Keller Atrium table 5. All other office hours are going to be on Zoom. The instructor's office hours are group office hours. The instructor's office hours will be on Zoom and will be recorded.
| Time | Mondays | Tuesdays | Wednesdays | Thursdays | Fridays |
| 11 am - 12 pm | - | Zach | Ethan | - | - |
| 12 pm - 1 pm | - | - | - | - | - |
| 1 pm - 2 pm | - | Ishan | Narek | Sean | - |
| 2 pm - 3 pm | Ishan | Ethan | - | Sai | - |
| 3 pm - 4 pm | - | Sai | Tushar | Tushar |
Ace |
| 4 pm - 5 pm | Mattia | Rishi | Ace | - | - |
| 5 pm - 6 pm | Mattia | Subhanga | - | - | - |
| Week | Date | Type | Topic |
| 1 | 09/07/2021 | Class | Course Introduction |
| 09/09/2021 | Class | Version Control Systems | |
| 09/10/2021 |
Lab | Lab 1: Git | |
| 2 |
09/13/2021 | Office Hours | - |
| 09/14/2021 | Class | Build Automation and Computing Environments | |
| 09/16/2021 | Class | Java | |
| 09/17/2021 | Lab | Lab 2: Gradle and Java | |
| 3 |
09/20/2021 | Office Hours | - |
| 09/21/2021 | Class | Software Design 1 | |
| 09/23/2021 | Class | Software Design 2 | |
| 09/24/2021 | Lab | Lab 3: UML Class Diagram | |
| 4 |
09/27/2021 | Office Hours | - |
| 09/28/2021 | Class | Testing 1 | |
| 09/30/2021 | Class | Debugging and IDEs | |
| 10/01/2021 | Lab | Lab 4: IDEA and JUnit | |
| 5 |
10/04/2021 | Office Hours | - |
| 10/05/2021 | Class | Software Documentation | |
| 10/07/2021 | Class | Software Refactoring | |
| 10/08/2021 | Lab | Lab 5: Checkstyle and Javadoc | |
| 6 |
10/11/2021 | Office Hours | - |
| 10/12/2021 | Project Class | Project Iteration 1 | |
| 10/14/2021 | Class | Team Building |
|
| 10/15/2021 | Project Lab | Lab 6: Project Iteration 1 | |
| 7 |
10/18/2021 | Office Hours | - |
| 10/19/2021 | Class | Design Patterns 1 | |
| 10/21/2021 | Class | Design Patterns 2 | |
| 10/22/2021 | Lab | Lab 7: Design Patterns | |
| 8 |
10/25/2021 | Office Hours | - |
| 10/26/2021 | Class | Bug Reporting and Triaging | |
| 10/28/2021 | Class | Code Reviews | |
| 10/29/2021 | Lab | Lab 8: GitHub Issues and Pull Requests |
|
| 9 |
11/01/2021 | Office Hours | - |
| 11/02/2021 | Project Class | Project Iteration 2 | |
| 11/04/2021 | Class | Program Representations | |
| 11/05/2021 | Project Lab | Lab 9: Project Iteration 2 | |
| 10 |
11/08/2021 | Office Hours | - |
| 11/09/2021 | Class | Black-box Testing | |
| 11/11/2021 | Class | White-box Testing | |
| 11/12/2021 | Lab | Lab 10: Jacoco | |
| 11 |
11/15/2021 | Office Hours | - |
| 11/16/2021 | Class | Test Doubles | |
| 11/18/2021 | Class | Topics in Debugging and Testing | |
| 11/19/2021 | Lab | Lab 11: Mockito | |
| 12 |
11/22/2021 | Office Hours | - |
| 11/23/2021 | Project Class | Project Iteration 3 | |
| 11/25/2021 | - | - | |
| 11/26/2021 | - | - | |
| 13 |
11/29/2021 | Office Hours | - |
| 11/30/2021 | Class | Android 1 | |
| 12/02/2021 | Class | Android 2 | |
| 12/03/2021 | Project Lab | Lab 12: Project Iteration 3 | |
| 14 |
12/06/2021 | Office Hours | - |
| 12/07/2021 | Class | Android Testing | |
| 12/09/2021 | Class | Software Engineering | |
| 12/10/2021 | Lab | Lab 13: Android | |
| 15 | 12/13/2021 | Office Hours | - |
| 12/14/2021 | Class | Guest Lecture |
You should refer to this course site and our Piazza site for finding information about course meetings, assignments, and grades. We will be meeting in class and lab but there is also the option to attend remotely on Zoom. The instructor will deliver class lectures and graduate TAs will deliver lab demonstrations. For class meetings, we will provide video recordings (when applicable). For lab meetings, we will provide video demonstrations (when applicable). We will use Piazza for all communications between students, the instructor, and the course staff. (The course staff added you to Piazza using your UMN email.) We use Piazza as it is a great place to promote interactions among students and the course staff can keep track of all course-related discussions in one place. Participation assessments will use Gradescope. Lab assignments will use GitHub classroom. Project iterations will use GitHub (https://github.com and not https://github.umn.edu). Quizzes will use Gradescope.
You can find all the assessment tasks on the Assignments page. Please check this page at the end of each course meeting for updated information.
Final course grades will be calculated based on the following percentages:
| Percentage | Assessment Type |
| 10% | Participation |
| 20% | Labs |
| 25% | Quizzes |
| 15% | Project Iteration I |
| 15% | Project Iteration II |
| 15% | Project Iteration III |
Participation: Attending classes in-person or on Zoom is not required but highly encouraged as it is the best way to keep up with the course. The course has a participation grade. The participation grade will be based on offline assessments that include questions already answered during class meetings. Specifically, at the end of each class meeting, you will need to complete a participation assessment on Gradescope. The assessment will be open for 48 hours after the class ends. For people that cannot attend course meetings synchronously, we will provide meeting recordings linked in the Topics table above.
Labs: There will be 13 labs. However, labs labeled with "Project Lab" will not be graded as their purpose is to get you started on the project. In total, ten labs will be graded but the lab with the lowest score will be automatically dropped from the final grade computation. Labs are individual assignments and you are not allowed to collaborate to identify the solution.
Quizzes: There will be six quizzes in the course. The quiz with the lowest score will be automatically dropped from the final grade computation. Quizzes will be available for 48 hours after they are released but once you start them they will be open for a limited amount of time. The time limit of the quiz is 30 min. Quizzes will happen every other week and will be based on the topics of the previous two weeks (unless otherwise notified). To provide an example, the first quiz of the course will open on Tuesday 09/21/2021, and will be based on the topics covered in weeks 1 and 2.
Project Iterations: In the project iterations, you will be working in a team of three people. We will use peer evaluations to help us assess how much the individual team members contributed to the results of the team. Please note that we will (1) give a lower weight to outliers (e.g., discount one very negative rating when all other ratings for that student are positive), (2) consider individual cases (e.g., specific problems that might have affected the performance), and (3) provide the opportunity to detail the individual contributions to the project iterations. In general, we will use a grain of salt when taking the ratings into account.
Exams: There is no midterm or final exam.
Late work is not accepted in this class. There are a few reasons for this policy. First, the assessment schedule follows a tight timeline and we would like to grade assessments as quickly as possible. Second, you will have ample time to complete the assessments. Third, the majority of the assessments will help you complete immediately following assessments. Finally, for project iterations, we will release solutions so that students can keep pace in all iterations.
Requests for items to be regraded must be made within seven calendar days of the marks being posted. Be aware, this means that students may not ask for an assignment from early in the term be regraded after they receive their final grade. If a mistake has been made in recording a student's marks, please bring this to the attention of the course staff prior to the end of the term.
Final grades will be assigned based on the following scale. Grading for this course is on an absolute scale (i.e. no curve, no rounding up, etc.).
| Weighted Score (x) | Letter Grade | S/N |
| 94.0% ≤ x ≤ 100.0% | A | S |
| 90.0% ≤ x < 94.0% | A- | S |
| 87.0% ≤ x < 90.0% | B+ | S |
| 83.0% ≤ x < 87.0% | B | S |
| 80.0% ≤ x < 83.0% | B- | S |
| 77.0% ≤ x < 80.0% | C+ | S |
| 73.0% ≤ x < 77.0% | C | S |
| 70.0% ≤ x < 73.0% | C- | S |
| 65.0% ≤ x < 70.00 | D+ | N |
| 60.0% ≤ x < 65.0% | D | N |
| 0% ≤ x < 60.0% | F | N |
I also would like to share some of my thoughts on final grades. First and foremost, your grade isn't a judgment of who you are as a person. It is not an overarching statement about your fitness for work in this major or this field. It is not even necessarily a statement about how much of the course material you know or how hard you tried. It is a summary of the record of how you did on the required assessments for this course.
Second, if you mention to me that you think that your grade doesn't reflect your effort or your understanding, I want to let you know that I understand that. I want to let you know that you are so much more than that number or letter on a page. But if you ask me whether it is possible to change your grade, please understand that you are asking me to falsify the record of how you did on the required assessments for this course. I cannot do that. I can tell you that even if your grade is not what you would have hoped it would be, I still believe in you and in the dream behind that hope. I 100% believe that you can go on to be successful in this major and in the field throughout your life.
To ensure the health and safety of everyone during these difficult times, the following precautions will be taken in this course.
Masking, vaccination, and absences: The University of Minnesota currently requires all students, staff, and faculty to wear masks when indoors regardless of vaccination status. On August 24, 2021, the University launched a vaccine attestation process for faculty and staff, and on August 27, 2021, launched a vaccine requirement process for students - see the Get the Vax 2.0 initiative. Please stay at home if you experience symptoms of COVID-19 or have a positive COVID-19 test result and consult with your healthcare provider about an appropriate course of action. For COVID-19 excused absences, I will work with you to find the best course of action for missed work and/or class experiences.
Stable seating: The University recommends that students try to sit in the same seat for every lecture. This will facilitate contact tracing in the unfortunate event someone tests Covid-positive during the semester.
Interactions: Other than the lectures, the interactions with the instructor will be over Piazza or Zoom. During the lectures, I would greatly appreciate it if we could practice social distancing while interacting. I am very happy to answer questions at end of the class while maintaining the CDC recommended social distancing guidelines and I will make sure to stay a few minutes longer at the end of class so that you can ask questions also from your seat. If you would like to discuss something in private, please contact me on Piazza, and I will take it from there.
Eating and drinking: Eating during class and the labs might make the masking precaution ineffective. For this reason, it will not be possible to consume food (with the exception of drinks) during the class and lab meetings. When drinking, masks must be worn between sips. If you have a medical exemption that requires you to eat or drink in class, do not hesitate to contact the instructor and/or provide an accommodation letter through DRC.
While this setup is far from ideal, every effort will be made to make the course as accessible, engaging, and useful as possible. Thank you for your understanding and cooperation.
CSCI2021 and CSCI2041 are the formal prerequisites for this class. You must be accepted to the CS upper division, be a CS graduate student, or receive department permission. You are expected to have some previous experience programming in Java. You are expected to know basic data structures (such as lists), algorithms (such as search), recursion, and data abstraction. You are expected to be proficient in English and using a computer to produce text documents and figures as required by the writing assignments. Please contact the instructor on Piazza if you have any questions about whether the course is a good fit for your background and academic goals.
In this course, you will learn the theory, skills, and tools to become a good software developer. This course will prepare you to succeed in 4xxx- and 5xxx-level programming intensive courses. CSCI3081W is a required course in the computer science undergraduate curriculum. The topics covered in the course include:
In this course, you will learn to:
This course covers a large amount of material, requires significant programming and other development activities, and is writing intensive. Therefore the course will require a good amount of time to do all the reading, programming, project development, studying for quizzes, and writing. Students should expect to spend an average of 12 to 15 hours a week on this course.
In previous courses, you’ve learned about different programming languages, algorithms, and data structures, and you’ve written programs as part of your course assignments. But, there’s a big difference between writing a function or two to plug into a homework assignment and the type of programming that happens in the "real-world"– for example, in the type of work you may do in industry or graduate school in a few years. One of the major goals of this class is to provide a first academic experience with analyzing, designing, writing, and verifying a “big” program – one that requires working on a project that takes more than a month to complete, requires a significant number (greater than 10) separate files of software code rather than one or two, and requires documentation and other good programming practices in order to be successful. In this course, you’ll learn how to do all these things through hands-on practice.
Project topic: This semester, we will be working on a fun visual project involving simulation and visualization of a transportation system. You’ll start by augmenting the base simulation. Later in the semester, you will extend it to use various software patterns to configure the simulation, visualize simulation during execution, and analyze the results. You will also use techniques to ensure that the software behaves as expected.
In the labs, you will use real-world technologies that implement the theoretical concepts studied in class. The labs will also prepare you for doing well in the project.
The first priority of the course staff (i.e., TAs) is to ensure that each student receives the support they need to understand the course content. The course staff forms the first line of support when it comes to the labs and the project iterations. Please see them first with any questions about the course content and project iteration details.
There is no required textbook and the course meetings together with the course's slides will help you prepare for the assessments. There are a few books that we suggest if you would like to further explore some of the concepts we will cover throughout the course. The books are the followings:
All work submitted for this course is required to be your original work, or that of your group in the case of group work. You are expected to do your own thinking about how to solve an assignment, your own design, and your own coding. You are encouraged to discuss the content of the lectures and the texts with your peers. If you have any questions about whether discussing something with peers might go beyond what is permitted, then stop and ask us first on Piazza for clarification on the policy.
You are also not allowed to post your solutions to repos that are not the one we assigned to you. We will also use code plagiarism detectors in this class.
The web is a fantastic resource for learning about programming, but it is also a potential source for solutions to assignments, so it is important that we are all on the same page with regard to what is a permitted use of an online resource for this class and what is not. Use of the web in a way that supplements the type of information you will find in your class materials is great. This is encouraged. For example, if we talk about the Factory Method Design Pattern in class, you are encouraged to search for "factory method design pattern" online and read more about this as a generic technique that can be used within many programs. However, when it comes to programming a solution to your project, you are not allowed to search online for something like "use factory method design pattern to a bus factory. This crosses a line into searching out the solution to an assignment rather than learning about design patterns.
Scholastic dishonesty includes any deceptive means whereby a student attempts to gain an unfair advantage. Examples of scholastic dishonesty include violating the course policies outlined here, especially its “Academic Integrity” section; plagiarizing; cheating on assignments or examinations; or engaging in unauthorized collaboration on academic work, either with other students or via the internet. In order to be as clear as possible about your scholastic conduct responsibilities and how these relate specifically to the types of courses that we teach in the Department of Computer Science & Engineering, the faculty have prepared a CS&E Department Academic Conduct Policy. Our course will follow this policy, which stands alongside the broader Board of Regents Student Conduct Code.
Within the course, a student responsible for scholastic dishonesty can be given a penalty, including an "F" or "N" for the course. I am also required to report any incident to the Office for Student Conduct and Academic Integrity, and further disciplinary action may occur.
You are responsible for knowing and following the policies on scholastic conduct that are described in the syllabus and in the related documents discussed above (see especially the CS&E Department Academic Conduct Policy).
University policy is to provide, on a flexible and individualized basis, reasonable accommodations to students who have documented disability conditions (e.g., physical, learning, psychiatric, vision, hearing, or systemic) that may affect their ability to participate in course activities or to meet course requirements. Students with disabilities are encouraged to contact Disability Services and their instructors to discuss individual needs for accommodations. Disability Services, McNamara Alumni Center, Suite 180, 200 Oak Street, East Bank. Staff can be reached by calling (612) 626-1333 (voice or TTY).
As a student you may experience a range of issues that can cause barriers to learning, such as strained relationships, increased anxiety, alcohol/drug problems, feeling down, difficulty concentrating, and/or lack of motivation. These mental health concerns or stressful events may lead to diminished academic performance or reduce your ability to participate in daily activities. University of Minnesota services are available to assist you with addressing these and other concerns you may be experiencing. You can learn more about the broad range of confidential mental health services available on campus here.
In this course, we are committed to the University's equal access and opportunity policy. The University of Minnesota shall provide equal access to and opportunity in its programs, facilities, and employment without regard to race, color, creed, religion, national origin, gender, age, marital status, disability, public assistance status, veteran status, sexual orientation, gender identity, or gender expression.
In this course, we are committed to the University's Sexual Harassment, Sexual Assault, Stalking and Relationship Violence policy. The University of Minnesota is committed to taking prompt and effective steps intended to end sexual harassment, sexual assault, stalking, relationship violence, and related retaliation, prevent their recurrence and, as appropriate, remedy their effects.
Zoom: We will use Zoom for classes and labs to allow remote attendance. We will also use Zoom for office hours meetings. To enhanche the student learning experience, we will record the meetings, use Kaltura to generate subtitles, and provide the recordings on this site. (We will not make the recordings publicly available.) If you have concerns about your visibility on Zoom (e.g., your video on Zoom) while attending meetings remotely, you are free to turn off your video during the meetings, and you should not be visible in the recording. If you have other concerns, please contact the instructor on Piazza for further information.
Websites: In this course, our use of technology will involve sharing students' names, UMN usernames, and/or coursework information to course-related websites (e.g., Gradescope). All web sites might be affected by security vulnerabilities and it could be possible for them to be the target of software attacks. If you have concerns about the visibility of your name, username, or other information, please contact the instructor on Piazza for further information. Rest assured that it is our priority to keep this information within the boundaries of these websites.
All students are expected to behave as scholars at a leading institute of technology. This includes not talking over each other during the meetings. Disruptive students will be warned and potentially dismissed from the meetings.
We reserve the right to make changes to the syllabus to accommodate for exceptional circumstances that are out of the course staff's control. We will announce any change if it needs to happen.