activity
20242026
collaborators

6 papers

cs.SE2026

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…

cs.SE2026

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…

cs.SE2025

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…

cs.SE2024

SDPERL: A Framework for Software Defect Prediction Using Ensemble Feature Extraction and Reinforcement Learning

Mohsen Hesamolhokama, Amirahmad Shafiee, Mohammadreza Ahmaditeshnizi +2

Ensuring software quality remains a critical challenge in complex and dynamic development environments, where software defects can result in significant operational and financial r…

q-fin.ST2024

A Decision Support System for Stock Selection and Asset Allocation Based on Fundamental Data Analysis

Ali Abrishami, Jafar Habibi, AmirAli Jarrahi +2

Financial markets are integral to a country's economic success, yet their complex nature raises challenging issues for predicting their behaviors. There is a growing demand for an…

cs.CV2024

Emo3D: Metric and Benchmarking Dataset for 3D Facial Expression Generation from Emotion Description

Mahshid Dehghani, Amirahmad Shafiee, Ali Shafiei +6

Existing 3D facial emotion modeling have been constrained by limited emotion classes and insufficient datasets. This paper introduces "Emo3D", an extensive "Text-Image-Expression d…