4 papers
KG-Commit: A Dynamic Knowledge Graph for Online Just-in-Time Software Defect Prediction
Mohsen Hesamolhokama, Mohammad Sina Beyrami Aghbash, Behnam Rohani +2
Just-in-time software defect prediction (JIT-SDP) aims to identify risky commits as they arrive and provide developers with timely feedback. This need for low latency has led most…
Learning Spectral Representations of Code through Latent Graph Learning for Generalizable Cross-Language Code Clone Detection
Mohsen Hesamolhokama, Ali Sadeghi, Kousha Moeini +3
Current code clone detection (CCD) methods rely on fixed, language-specific graph representations like abstract syntax trees (ASTs) or program dependency graphs (PDGs). Because fun…
From Illusion to Insight: Change-Aware File-Level Software Defect Prediction Using Agentic AI
Mohsen Hesamolhokama, Behnam Rohani, Amirahmad Shafiee +2
Much of the reported progress in file-level software defect prediction (SDP) is, in reality, nothing but an illusion of accuracy. Over the last decades, machine learning and deep l…
ClickTree: A Tree-based Method for Predicting Math Students' Performance Based on Clickstream Data
Narjes Rohani, Behnam Rohani, Areti Manataki
The prediction of student performance and the analysis of students' learning behavior play an important role in enhancing online courses. By analysing a massive amount of clickstre…