A recent study has shown that 25% of technical assessments display signs of plagiarism. To ensure assessment integrity, companies use plagiarism detection, but it has its flaws. The current standard method of MOSS code similarity has a reputation for false positives, particularly for simpler coding challenges. However, the AI tool ChatGPT has shown to be effective at evading MOSS code similarity detection.
ChatGPT is able to offer unique approaches to certain questions, and its transformer-based model generates different answers every time. This gives it an advantage in bypassing code similarity detection. Therefore, MOSS code similarity checks can be easily bypassed with ChatGPT.
This raises the question of whether technical assessments can still be trusted. The compromise between effectiveness and candidate experience has always been a problem for plagiarism detection. Relying on any single point of analysis like MOSS Code Similarity, effectively means it only detects patterns in the code that could be plagiarism.
HackerRank has rethought plagiarism detection altogether. They built an AI model that analyses dozens of signals, including aspects of the candidate’s coding behavior. Their AI-powered plagiarism detection system boasts a 93% accuracy rate, and it repeatedly detects ChatGPT-generated solutions. It is a learning model which will become more accurate over time. Hiring managers can even replay the answer keystroke by keystroke to confirm suspicious activity.
Due to their advanced plagiarism detection system, HackerRank provides an assessment experience that is fair to both the candidate and the hiring team. Plagiarism detection in the AI era requires companies to scramble for better versions of MOSS, more complex questions and different types. But at HackerRank, their new approach sets a standard that analyzes the candidate’s coding behavior rather than simply looking for similarities, ensuring assessment integrity is upheld.
Frequently Asked Questions (FAQs) Related to the Above News
What is ChatGPT?
ChatGPT is an AI tool that offers unique approaches to technical assessment questions, allowing it to evade MOSS code similarity detection.
What is MOSS code similarity?
MOSS code similarity is the current standard method used for plagiarism detection in technical assessments. It checks for patterns in the code that could be plagiarism.
Why is MOSS code similarity not a reliable method for plagiarism detection?
MOSS code similarity has a reputation for false positives, especially for simpler coding challenges.
How does ChatGPT bypass code similarity detection?
ChatGPT's transformer-based model generates different answers every time, allowing it to evade MOSS code similarity detection.
Can technical assessments still be trusted?
Technical assessments can still be trusted, but companies need to use advanced plagiarism detection systems that analyze multiple signals, including coding behavior, rather than relying solely on MOSS code similarity.
How accurate is HackerRank's AI-powered plagiarism detection system?
HackerRank's AI-powered plagiarism detection system has a 93% accuracy rate.
What does HackerRank's advanced plagiarism detection system analyze?
HackerRank's advanced plagiarism detection system analyzes dozens of signals, including coding behavior, to ensure assessment integrity is upheld.
Can hiring managers confirm suspicious activity with HackerRank's system?
Yes, hiring managers can replay the answer keystroke by keystroke to confirm suspicious activity.
What is the advantage of HackerRank's plagiarism detection system?
HackerRank's plagiarism detection system provides an assessment experience that is fair to both the candidate and the hiring team.
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
