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Instructors have limited time and resources to help struggling students, and these resources should be directed to the students who most need them. To address this, researchers have constructed models that can predict students' final course…

Machine Learning · Computer Science 2021-02-12 Ge Gao , Samiha Marwan , Thomas W. Price

Recent advances in large language models (LLMs) have shown that test-time scaling can substantially improve model performance on complex tasks, particularly in the coding domain. Under this paradigm, models use a larger token budget during…

Artificial Intelligence · Computer Science 2026-04-21 Jiaxin Fang , Runyuan He , Sahil Bhatia , Neel Gajare , Alvin Cheung

The most common method to auto-grade a student's submission in a CS1 or a CS2 course is to run it against a pre-defined test suite and compare the results against reference results. However, this technique cannot be used if the correctness…

Artificial Intelligence · Computer Science 2024-10-22 Aaryen Mehta , Gagan Aryan

Software developers use metrics to evaluate code quality and productivity, but these practices are still rare in programming education. This project bridges the gap by collecting real-time learning analytics from individual student and…

Performance analysis has always been an afterthought during the application development process, focusing on application correctness first. The learning curve of the existing static and dynamic analysis tools are steep, which requires…

Machine Learning · Computer Science 2021-04-23 Nathan Pinnow , Tarek Ramadan , Tanzima Z. Islam , Chase Phelps , Jayaraman J. Thiagarajan

Survival analysis studies and predicts the time of death, or other singular unrepeated events, based on historical data, while the true time of death for some instances is unknown. Survival trees enable the discovery of complex nonlinear…

Machine Learning · Computer Science 2024-01-10 Tim Huisman , Jacobus G. M. van der Linden , Emir Demirović

As programmers write code, they often edit and retry multiple times, creating rich "interaction traces" that reveal how they approach coding tasks and provide clues about their level of skill development. For novice programmers in…

Machine Learning · Computer Science 2026-04-16 Alexis Ross , Megha Srivastava , Jeremiah Blanchard , Jacob Andreas

This paper investigates the execution of tree-shaped task graphs using multiple processors. Each edge of such a tree represents some large data. A task can only be executed if all input and output data fit into memory, and a data can only…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-10-02 Lionel Eyraud-Dubois , Loris Marchal , Oliver Sinnen , Frédéric Vivien

Background and Context: Some skills taught in introductory programming courses are categorized into 1) explaining code, 2) arranging lines of code in correct sequence, 3) tracing through the execution of a program, and 4) writing code from…

Human-Computer Interaction · Computer Science 2026-03-04 Dip Kiran Pradhan Newar , Max Fowler , David H. Smith , Seth Poulsen

Dynamic analyses are a standard approach to analyzing and testing concurrent programs. Such techniques observe program traces and analyze them to infer the presence or absence of bugs. At its core, each analysis maintains a partial order…

Programming Languages · Computer Science 2024-04-01 Hünkar Can Tunç , Ameya Prashant Deshmukh , Berk Çirisci , Constantin Enea , Andreas Pavlogiannis

Program comprehension is a fundamental task in software development and maintenance processes. Software developers often need to understand a large amount of existing code before they can develop new features or fix bugs in existing…

Machine Learning · Computer Science 2019-10-29 Vinoj Jayasundara , Nghi Duy Quoc Bui , Lingxiao Jiang , David Lo

This paper investigates the execution of tree-shaped task graphs using multiple processors. Each edge of such a tree represents a large IO file. A task can only be executed if all input and output files fit into memory, and a file can only…

Distributed, Parallel, and Cluster Computing · Computer Science 2012-10-10 Loris Marchal , Oliver Sinnen , Frédéric Vivien

In recent years, deep learning techniques have been developed to improve the performance of program synthesis from input-output examples. Albeit its significant progress, the programs that can be synthesized by state-of-the-art approaches…

Machine Learning · Computer Science 2018-03-09 Xinyun Chen , Chang Liu , Dawn Song

Monitoring in-class programming exercises can help instructors identify struggling students and common challenges. However, understanding students' progress can be prohibitively difficult, particularly for multi-faceted problems that…

Human-Computer Interaction · Computer Science 2026-02-02 Yinuo Yang , Ashley Ge Zhang , Steve Oney , April Yi Wang

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these…

Logic in Computer Science · Computer Science 2025-09-16 Umang Mathur , Andreas Pavlogiannis , Hünkar Can Tunç , Mahesh Viswanathan

We propose a novel method for automatic program synthesis. P-Tree Programming represents the program search space through a single probabilistic prototype tree. From this prototype tree we form program instances which we evaluate on a given…

Artificial Intelligence · Computer Science 2017-07-13 Christian Oesch

The purpose of this research is to study the possibility of identifying students, statistically, by analyzing their behavior in different consecutive activities. In this project, there are three different sorts of activities: animated…

Social and Information Networks · Computer Science 2019-04-05 Abdulelah Abuabat , Peter Brusilovsky

Programming in Prolog is hard for programmers that are used to procedural coding. In this manual the method of drawing search trees is introduced with the aim to get a better understanding of how Prolog works. After giving a first example…

Programming Languages · Computer Science 2020-01-23 Johan Bos

Reading and understanding code are fundamental skills for novice programmers, and especially important with the growing prevalence of AI-generated code and the need to evaluate its accuracy and reliability. ``Explain in Plain English''…

Computers and Society · Computer Science 2025-03-18 David H. Smith , Max Fowler , Paul Denny , Craig Zilles

Offering rich contexts to Large Language Models (LLMs) has shown to boost the performance in various tasks, but the resulting longer prompt would increase the computational cost and might exceed the input limit of LLMs. Recently, some…

Computation and Language · Computer Science 2025-09-30 Wenhao Mao , Chengbin Hou , Tianyu Zhang , Xinyu Lin , Ke Tang , Hairong Lv
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