Academic Honesty

The University of Chicago has a formal academic integrity policy, and all students are expected to follow it. This page explains how that policy applies in CMSC 141 and describes the standards we use when evaluating academic honesty.

The most serious academic integrity violation in this course is plagiarism: submitting work that is not your own, whether it comes from another student, the internet, or a generative AI tool. We take plagiarism seriously and report all violations to the College according to university policy.

Academic integrity cases are unpleasant for everyone involved and can result in significant academic penalties, including failure in the course.

How Plagiarism Is Detected

Many students assume plagiarism can be hidden by changing variable names, rearranging code, or modifying small details. In practice, these techniques are rarely effective.

We use automated tools that compare submissions across all sections of the course as well as submissions from previous offerings. Any similarities flagged by these tools are reviewed manually by the instructional staff.

If you submit work based on someone else's code, there is a substantial chance that it will be detected.

Never Do These Things

The following actions are always prohibited:

• Do not ask another student to show you their code. It does not matter whether you only want inspiration or a hint. Looking at another student's solution is not permitted.
• Do not show your code to another student. If you share your work and someone else uses it, both students may be held responsible for the violation.
• Do not post your code publicly. This includes public GitHub repositories, GitHub Gists, Pastebin, Discord servers, Reddit posts, and similar services. Use only the private GitHub repositories provided for the course.
• Do not use generative AI tools while completing assignments. This includes ChatGPT, GitHub Copilot, Claude, Gemini, and similar tools. Using AI-generated code, debugging assistance, solution strategies, or assignment-specific explanations is not permitted.
• Do not paste assignment text or starter code into AI tools. Assignment materials and course code should never be submitted to generative AI systems or similar services.

After the Course Ends

The restrictions on sharing your work continue after the course is over.

You should never post your solutions publicly, even after completing the course, graduating, or leaving the university. Future students deserve the opportunity to complete the assignments on their own.

The one exception is that you may privately share your work with a prospective employer who requests code samples during an application or interview process.

Be Careful With These Activities

The following activities are not automatically violations, but they can easily cross the line into academic dishonesty if handled carelessly.

• Using code found online. While some online resources can be valuable references, incorporating code from external sources creates a risk of plagiarism. Any outside source must be properly cited.
• Forming study groups for homework. Study groups can be useful for reviewing course material, but assignments should ultimately be completed independently.
• Discussing assignments. Discussions should focus on high-level concepts and understanding the problem. Conversations should not include implementation details or shared code.
• Whiteboarding solutions. Sketching detailed solutions or pseudocode with other students can become problematic. Use collaborative discussions to understand the problem, then write your own solution independently.

These situations do not automatically constitute plagiarism, but they often lead to violations. When in doubt, err on the side of caution.

Always Cite Your Sources

If you receive help or consult outside resources, acknowledge them.

• If you discussed part of an assignment with another student, include a comment in your source file identifying who you spoke with.
• If you consulted an outside resource, cite it in a comment at the top of your file.
• Do not copy code verbatim from external sources.
• Do not rely on sources that provide complete or nearly complete solutions.
• If an online example influenced your solution, cite it even if your final code differs substantially from the example.

You do not need to cite the course textbook or the official Python documentation, provided you are not copying substantial blocks of code from those sources.

If You Feel Desperate

Many academic integrity violations occur because students feel overwhelmed, stressed, or trapped by an approaching deadline.

If that happens, ask for help instead.

Talk to the instructional staff. Visit office hours. Post on Ed. Email the instructor. A poor performance on a single assignment is recoverable. Plagiarism is not.

This course is designed so that one difficult week does not determine your final grade. Academic dishonesty is never worth the risk.

Consequences of Violations

Violations of this policy carry substantial consequences.

At minimum, a violation may result in a significant reduction in the final course grade. More serious violations may result in failure of the course.

All violations are reported to the College, which may impose additional disciplinary sanctions independent of the course grade.

Students found responsible for academic dishonesty may also lose eligibility for options such as withdrawal or Pass/Fail conversion, subject to university policy and administrative decisions.

Questions

If you are unsure whether something is allowed, ask before doing it.

We would much rather answer a question about academic integrity than discover a problem after an assignment has been submitted.