Abstract
When student programs are compared for similarity, certain segments of code are always sure to be similar. Some of these segments are boilerplate code - public static void main String [] args and the like - and some will be code that was provided to students as part of the assessment specification. The purpose of this working group is to explore what other code is expected to be reasonably common in student assessments, and should therefore be excluded from similarity checking. The answers will clearly vary with programming language, and perhaps with level of assessment item. Working group members will collect assessment submissions from their own or their colleagues' students, and it is hoped that these submissions will together encompass a wide variety of assessment tasks in a wide variety of programming languages. The working group aims to deliver clear guidelines as to what code can reasonably be excluded from automatic code similarity detection in various circumstances. It also aims to deliver a summary of what sort of code lecturers tend to provide for students when setting an assigned task, and why they provide that code.
Original language | English |
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Title of host publication | Proceedings of the 2020 ACM Conference on Innovation and Technology in Computer Science Education |
Editors | Andrew Luxton-Reilly, Monica Divitini |
Place of Publication | New York NY USA |
Publisher | Association for Computing Machinery (ACM) |
Pages | 500-501 |
Number of pages | 2 |
ISBN (Electronic) | 9781450368742 |
DOIs | |
Publication status | Published - Jun 2020 |
Event | Annual Conference on Innovation and Technology in Computer Science Education 2020 - Trondheim, Norway Duration: 15 Jun 2020 → 19 Jun 2020 Conference number: 25th https://iticse.acm.org (Website) https://dl.acm.org/doi/proceedings/10.1145/3341525 (Proceedings) |
Conference
Conference | Annual Conference on Innovation and Technology in Computer Science Education 2020 |
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Abbreviated title | ITiCSE 2020 |
Country/Territory | Norway |
City | Trondheim |
Period | 15/06/20 → 19/06/20 |
Internet address |
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Keywords
- academic integrity
- code similarity detection
- collusion
- Plagiarism