Friday, June 12, 2020

[DMANET] [CFP] Authorship Identification of SOurce COde (AI-SOCO) Task @ FIRE2020

[Apologies for multiple postings]
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Authorship Identification of SOurce COde (AI-SOCO)
Website: https://sites.google.com/view/ai-soco-2020/

To be organized at FIRE 2020 (http://fire.irsi.res.in/fire/2020/home)
10 - 13 December
Virtual Conference
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Task Description:
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General authorship identification is essential to the detection of
undesirable deception of others' content misuse or exposing the owners of
some anonymous hurtful content. This is done by revealing the author of
that content. Authorship Identification of SOurce COde (AI-SOCO) focuses on
uncovering the author who wrote some piece of code. This facilitates
solving issues related to cheating in academic, work and open source
environments. Also, it can be helpful in detecting the authors of malware
softwares over the world.

The dataset is composed of source codes collected from the open submissions
in the Codeforces online judge. Codeforces is an online judge for hosting
competitive programming contests such that each contest consists of
multiple problems to be solved by the participants. A Codeforces
participant can solve a problem by writing a solution for it using any of
the available programming languages on the website, and then submitting the
solution through the website. The solution's result can be correct
(accepted) or incorrect (wrong answer, time limit exceeded, etc.).

In our dataset, we selected 1000 users and collected 100 source codes from
each one. So, the total number of source codes is 100,000. All collected
source codes are correct and written using the C++ programming language.
For each user, all collected source codes are from unique problems.

Given the pre-defined set of source codes and their writers, the task
participants should build systems that are able to detect the writer given
any new, unseen before source codes from the previously defined writers
list.

Full task description can be found at:
https://sites.google.com/view/ai-soco-2020/


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Timeline
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8th June - Open track websites
8th June – Training and development data release
31st July – Test data release
7th September – Run submission deadline
20th September – Results declared
31st October – Working notes and overview papers due (tentative)
10th-13th December - FIRE 2020


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Organizers
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Ali Fadel, Jordan University of Science and Technology, Jordan
Husam Musleh, Jordan University of Science and Technology, Jordan
Ibraheem Tuffaha, Jordan University of Science and Technology, Jordan
Mahmoud Al-Ayyoub, Jordan University of Science and Technology, Jordan
Yaser Jararweh, Duquesne University, USA
Elhadj Benkhelifa, Staffordshire University, UK
Paolo Rosso, Universitat Politècnica de València, Spain

For regular updates subscribe to our mailing list:
ai-soco-fire@googlegroups.com

Regards,
Organizers of the Authorship Identification of SOurce COde (AI-SOCO) Task

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