Important: Please read the following statement thoroughly.
If you have any questions, contact the instructor or the TAs immediately.
Collaboration Policy & Academic Integrity
Lecture Participation Polls
Responses to lecture participation polls will be used to earn incentives for the Data Structures course. Discussion of collaborative lecture participation polls with those seated around you is encouraged. However, if we find anyone submitting answers for or using the account of another individual, we will zero the lecture participation points of all involved students and report the incident to the Dean of Students.
Academic Integrity for Tests and Final Exam
The tests and final exam for this course will be completed individually. Copying, communicating, or using disallowed materials during a test is cheating, of course. Students caught cheating on a test will receive an F in the course and will be reported to the Dean of Students for further disciplinary action.
Collaboration Policy for Programming Labs
Collaboration is encouraged during the weekly programming labs. Students are allowed to talk through and assist each other with these programming exercises. Students may ask for help from each other, the graduate lab TA, and undergraduate programming mentors. But each student must write up and debug their own lab solutions on their own laptop and be prepared to individually present and discuss this work with the TA to receive credit for each checkpoint.
As a general guideline, students may look over each other's shoulders at their labmate's laptop screen during lab — this is the best way to learn about IDEs, code development strategies, testing, and debugging. However, looking should not lead to line-by-line copying. Furthermore, each student should retain control of their own keyboard. While being assisted by a classmate or a TA, the student should remain fully engaged on problem solving and ask plenty of questions. Finally, other than the specific files provided by the instructor, electronic files or file excerpts should not be shared or copied (by email, text, Dropbox, GitHub, or any other means).
Homework Collaboration Policy
Academic integrity is a complicated issue for individual programming assignments, but one we take very seriously. Students naturally want to work together, and it is clear they learn a great deal by doing so. Getting help is often the best way to interpret error messages and find bugs, even for experienced programmers. Furthermore, in-depth discussions about problem solving, algorithms, and code efficiency are invaluable and make us all better software engineers. In response to this, the following rules will be enforced for programming assignments:
Students may read through the homework assignment together and discuss what is asked by the assignment, examples of program input & expected output, the overall approach to tackling the assignment, possible high level algorithms to solve the problem, and recent concepts from lecture that might be helpful in the implementation.
Students are not allowed to work together in writing code or pseudocode. Detailed algorithms and implementation must be done individually. Students may not discuss homework code in detail (line-by-line or loop-by-loop) while it is being written or afterwards. In general, students should not look at each other's computer screen (or hand-written or printed assignment design notes) while working on homework. As a guideline, if an algorithm is too complex to describe orally (without dictating line-by-line), then sharing that algorithm is disallowed by the homework collaboration policy.
Students are allowed to ask each other for help in interpreting error messages and in discussing strategies for testing and finding bugs. First, ask for help orally, by describing the symptoms of the problem. For each homework, many students will run into similar problems and after hearing a general description of a problem, another student might have suggestions for what to try to further diagnose or fix the issue. If that doesn't work, and if the compiler error message or flawed output is particularly lengthy, it is okay to ask another student to briefly look at the computer screen to see the details of the error message and the corresponding line of code. Please see a TA during office hours if a more in-depth examination of the code is necessary.
Students may not share or copy code or pseudocode. Homework files or file excerpts should never be shared electronically (by email, text, LMS, Dropbox, GitHub, etc.). Homework solution files from previous years (either instructor or student solutions) should not be used in any way. Students must not leave their code (either electronic or printed) in publicly-accessible areas. Students may not share computers in any way for the duration of this course. Each student is responsible for securing their homework materials using all reasonable precautions. These precautions include: Students should password lock the screen when they step away from their computer. Homework files should only be stored on private accounts/computers with strong passwords. Homework notes and printouts should be stored in a locked drawer/room.
The software you write for your Data Structures homework assignments may never be published in a public repository on GitHub or on any other software sharing site. Contributing to open source projects and publishing personal software projects are excellent ways to demonstrate your skills to future employers. We encourage you to join the Rensselaer Center for Open Source Software (RCOS) and build an online portfolio of amazing work. However, your Data Structures homework assignments may not be part of that portfolio. Your Data Structures homework solutions will not impress recruiters. A strong semester grade in Data Structures, contributions to open-source software, independent non-course projects, undergraduate research, and acing the coding interview will land you a great summer internship!
Students may not show their code or pseudocode to other students as a means of helping them. Well-meaning homework help or tutoring can turn into a violation of the homework collaboration policy when stressed with time constraints from other courses and responsibilities. Sometimes good students who feel sorry for struggling students are tempted to provide them with "just a peek" at their code. Such "peeks" often turn into extensive copying, despite prior claims of good intentions.
Students may not receive detailed help on their assignment code or pseudocode from individuals outside the course. This restriction includes tutors, students from prior terms, friends and family members, internet resources, etc.
All collaborators (classmates, TAs, ALAC tutors, upperclassmen, students/instructor via LMS, etc.), and all of the resources (books, online reference material, etc.) consulted in completing this assignment must be listed in the README.txt file submitted with the assignment.
Homework Plagiarism Detection and Academic Dishonesty Penalty
We use an automatic code comparison tool to help spot homework assignments that have been submitted in violation of these rules. The tool takes all assignments from all sections and all prior terms and compares them, highlighting regions of the code that are similar. The plagiarism tool looks at core code structure and is not fooled by variable and function name changes or addition of comments and whitespace.
The instructor checks flagged pairs of assignments very carefully, to determine which students may have violated the rules of collaboration and academic integrity on programming assignments. When the instructor believes that an incident of academic dishonesty has occurred, the involved students are contacted and a meeting is scheduled. All students caught cheating on a programming assignment (both the copier and the provider) will be punished. For undergraduate students, the standard punishment for the first offense is a 0 on the assignment and a full letter grade reduction on the final semester grade. Furthermore, students with academic integrity violations will lose all late days and may not earn additional late days or early submission assignment extension incentives for future assignments. Students whose violations are more flagrant will receive a higher penalty. Undergraduate students caught a second time will receive an immediate F in the course, regardless of circumstances. Each incident will be reported to the Dean of Students.
Graduate students found to be in violation of the academic integrity policy for homework assignments on the first offense will receive an F in the course and will be reported both to the Dean of Students and to the chair of their home department with the strong advisement that they be ineligible to serve as a teaching assistant for any other course at RPI.
You are not allowed to publicly post or privately share your Data Structures code even after you complete the course. If code from students from Fall 2018 or later terms is ever found in a public repository (e.g., GitHub) or other online source or if that code matches the code submission of another student in a later term, all involved students will be reported to the Dean of Students and the Computer Science Department Head -- even if they are not currently registered for Data Structures, or not currently enrolled at RPI, or have graduated from RPI. The instructor may file a retroactive change of semester grade with the registrar for the Data Structures course. The instructor may also submit a takedown notice and violation of terms of service or copyright to the website host of the public repository.
Academic Dishonesty in the Student Handbook
Refer to the The Rensselaer Handbook of Student Rights and Responsibilities for further discussion of academic dishonesty. Note that: "Students found in violation of the academic dishonesty policy are prohibited from dropping the course in order to avoid the academic penalty."
Number of Students Found in Violation of the Policy
Historically, 5-10% of students are found to be in violation of the academic dishonesty policy each semester. Many of these students immediately admit to falling behind with the coursework and violating one or more of the rules above and if it is a minor first-time offense may receive a reduced penalty.