OpenCoderRank: AI-Driven Technical Assessments Made Easy
September 08, 2025 Β· Declared Dead Β· π arXiv.org
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Authors
Hridoy Sankar Dutta, Sana Ansari, Swati Kumari, Shounak Ravi Bhalerao
arXiv ID
2509.06774
Category
cs.SE: Software Engineering
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Organizations and educational institutions use time-bound assessment tasks to evaluate coding and problem-solving skills. These assessments measure not only the correctness of the solutions, but also their efficiency. Problem setters (educator/interviewer) are responsible for crafting these challenges, carefully balancing difficulty and relevance to create meaningful evaluation experiences. Conversely, problem solvers (student/interviewee) apply coding efficiency and logical thinking to arrive at correct solutions. In the era of Large Language Models (LLMs), LLMs assist problem setters in generating diverse and challenging questions, but they can undermine assessment integrity for problem solvers by providing easy access to solutions. This paper introduces OpenCoderRank, an easy-to-use platform designed to simulate technical assessments. It acts as a bridge between problem setters and problem solvers, helping solvers prepare for time constraints and unfamiliar problems while allowing setters to self-host assessments, offering a no-cost and customizable solution for technical assessments in resource-constrained environments.
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