Datasets
Open Access
Programming Homework Dataset for Plagiarism Detection
- Citation Author(s):
-
VedranLjubovic
University of Sarajevo - Submitted by:
- Vedran Ljubovic
- Last updated:
- Tue, 05/17/2022 - 22:21
- DOI:
- 10.21227/71fw-ss32
- Data Format:
- Link to Paper:
- License:
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Abstract
Dataset is intended for studying how student programming styles and usage of IDE differs between students who plagiarise their homework and students who solve them honestly.
Dataset includes homeworks submitted by students during two introductory programming courses (A and B) delivered during two years (2016 and 2017). A is delivered in C programming language, while B is delivered in C++. In addition to homeworks, dataset includes full traces of all student activity and keystrokes during homework development. These traces were generated by setting the IDE to "autosave" after 1 second of inactivity, after which the file was committed to a SVN repository. For size reason, these repositories were then processed into JSON files actually stored. In addition, IDE was configured to pass output from student programs, compiler, debugger, profiler and unit testing into separate invisible files which were also stored in this repository. Finally, dataset includes ground truth with homeworks which are assumed to be plagiarised because of high similarity and the fact that (one of) students failed to do "oral defense" of homework.
The archive provided consists of three parts:
SOURCE CODES:
Actual submitted homeworks by students (i.e. their source codes) are stored in folder "src". Subfolders of this folder are named after courses: A2016, A2017, B2016 and B2017. This further contain subfolders for individual assignments. On each course students were required to solve 16-22 assignments labeled "Z1/Z1", "Z1/Z2", "Z2/Z1" etc. Finally, in each folder are actual C or C++ files named after student (anonymized, so actual student names were replaced by strings in form "student1393").
TRACES:
IDE usage traces are stored in folder named "stats". Again, this folder is organized into subfolders named after courses. These folders contain files named after student (anonymized) with extension .stats and are in JSON format. Format of JSON files is described in readme.txt file.
GROUND TRUTH:
Ground truth lists students and groups of students that are considered to have involved in plagiarism due to code similarity and failure to deliver an "oral defense". There are three ground truth files. ground-truth-anon.txt contains full list of plagiarisms, ground-truth-static-anon.txt only those based on source code similarity, and ground-truth-dynamic-anon.txt only those based on failure to do an "oral defense". There is some overlap between the last two files. The format of the file is: homework assignment in the format:
- A2016/Z1/Z1
(dash, space, course name, slash, assignment name), followed by lists of anonymized names of students (such as "student3241") or groups of students who are mutually plagiarised separated by comma.
Dataset Files
plagiarism-dataset.tar.gz (1.20 GB)
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Comments
Nice
Thank you.
If you use this dataset in your work, please cite the following paper:
Ljubovic V, Pajic E, Plagiarism detection in computer programming using feature extraction from ultra-fine-grained repositories, IEEE Access, Vol. 8, pp. 96505-96514, 2020.
Thanks for sharing this!
Thank you.
If you use this dataset in your work, please cite the following paper:
Ljubovic V, Pajic E, Plagiarism detection in computer programming using feature extraction from ultra-fine-grained repositories, IEEE Access, Vol. 8, pp. 96505-96514, 2020.
Thank you! This will be useful.
Thank you.
If you use this dataset in your work, please cite the following paper:
Ljubovic V, Pajic E, Plagiarism detection in computer programming using feature extraction from ultra-fine-grained repositories, IEEE Access, Vol. 8, pp. 96505-96514, 2020.