CodeFlowLM: Incremental Just-In-Time Defect Prediction with Pretrained Language Models and Exploratory Insights into Defect Localization
Fuente:
arXiv
Saved in:
| Main Authors: | Monteiro, Monique Louise, Cabral, George G., OLiveira, Adriano L. I. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction?
by: Nam, Doha, et al.
Published: (2025)
by: Nam, Doha, et al.
Published: (2025)
Feature Importance in the Context of Traditional and Just-In-Time Software Defect Prediction Models
by: Haldar, Susmita, et al.
Published: (2024)
by: Haldar, Susmita, et al.
Published: (2024)
On the calibration of Just-in-time Defect Prediction
by: Shahini, Xhulja, et al.
Published: (2025)
by: Shahini, Xhulja, et al.
Published: (2025)
An Exploratory Study on Just-in-Time Multi-Programming-Language Bug Prediction
by: Li, Zengyang, et al.
Published: (2024)
by: Li, Zengyang, et al.
Published: (2024)
IRJIT: A Simple, Online, Information Retrieval Approach for Just-In-Time Software Defect Prediction
by: Sahar, Hareem, et al.
Published: (2022)
by: Sahar, Hareem, et al.
Published: (2022)
Multimodal Learning for Just-In-Time Software Defect Prediction in Autonomous Driving Systems
by: Mohammad, Faisal, et al.
Published: (2025)
by: Mohammad, Faisal, et al.
Published: (2025)
Bridging Expert Knowledge with Deep Learning Techniques for Just-In-Time Defect Prediction
by: Zhou, Xin, et al.
Published: (2024)
by: Zhou, Xin, et al.
Published: (2024)
Just-In-Time Software Defect Prediction via Bi-modal Change Representation Learning
by: Jiang, Yuze, et al.
Published: (2024)
by: Jiang, Yuze, et al.
Published: (2024)
XMENTOR: A Rank-Aware Aggregation Approach for Human-Centered Explainable AI in Just-in-Time Software Defect Prediction
by: Roy, Saumendu, et al.
Published: (2026)
by: Roy, Saumendu, et al.
Published: (2026)
Defects4Log: Benchmarking LLMs for Logging Code Defect Detection and Reasoning
by: Wang, Xin, et al.
Published: (2025)
by: Wang, Xin, et al.
Published: (2025)
Comment Traps: How Defective Commented-out Code Augment Defects in AI-Assisted Code Generation
by: Huang, Yuan, et al.
Published: (2025)
by: Huang, Yuan, et al.
Published: (2025)
Building Defect Prediction Models by Online Learning Considering Defect Overlooking
by: Fedorov, Nikolay, et al.
Published: (2024)
by: Fedorov, Nikolay, et al.
Published: (2024)
Refactoring $\neq$ Bug-Inducing: Improving Defect Prediction with Code Change Tactics Analysis
by: Niu, Feifei, et al.
Published: (2025)
by: Niu, Feifei, et al.
Published: (2025)
Understanding Defects in Generated Codes by Language Models
by: Esfahani, Ali Mohammadi, et al.
Published: (2024)
by: Esfahani, Ali Mohammadi, et al.
Published: (2024)
BAFLineDP: Code Bilinear Attention Fusion Framework for Line-Level Defect Prediction
by: Qiu, Shaojian, et al.
Published: (2024)
by: Qiu, Shaojian, et al.
Published: (2024)
Scalable Defect Detection via Traversal on Code Graph
by: Liu, Zhengyao, et al.
Published: (2024)
by: Liu, Zhengyao, et al.
Published: (2024)
The Impact of Defect (Re) Prediction on Software Testing
by: Murakami, Yukasa, et al.
Published: (2024)
by: Murakami, Yukasa, et al.
Published: (2024)
A Defect Taxonomy for Infrastructure as Code: A Replication Study
by: Oliveira, Wendell, et al.
Published: (2025)
by: Oliveira, Wendell, et al.
Published: (2025)
From Illusion to Insight: Change-Aware File-Level Software Defect Prediction Using Agentic AI
by: Hesamolhokama, Mohsen, et al.
Published: (2025)
by: Hesamolhokama, Mohsen, et al.
Published: (2025)
An Audit of Machine Learning Experiments on Software Defect Prediction
by: Destefanis, Giuseppe, et al.
Published: (2026)
by: Destefanis, Giuseppe, et al.
Published: (2026)
Cascade Generalization-based Classifiers for Software Defect Prediction
by: Bashir, Aminat, et al.
Published: (2024)
by: Bashir, Aminat, et al.
Published: (2024)
BioDefect: The First Dataset for Defect Detection in Bioinformatics Software
by: Xu, Tianxiang, et al.
Published: (2026)
by: Xu, Tianxiang, et al.
Published: (2026)
Retrospective: Data Mining Static Code Attributes to Learn Defect Predictors
by: Menzies, Tim
Published: (2025)
by: Menzies, Tim
Published: (2025)
Defect Category Prediction Based on Multi-Source Domain Adaptation
by: Xing, Ying, et al.
Published: (2024)
by: Xing, Ying, et al.
Published: (2024)
Critical Considerations on Effort-aware Software Defect Prediction Metrics
by: Lavazza, Luigi, et al.
Published: (2025)
by: Lavazza, Luigi, et al.
Published: (2025)
A Joint Learning Framework for Bridging Defect Prediction and Interpretation
by: Xu, Guifang, et al.
Published: (2025)
by: Xu, Guifang, et al.
Published: (2025)
Toward Realistic Evaluations of Just-In-Time Vulnerability Prediction
by: Nguyen, Duong, et al.
Published: (2025)
by: Nguyen, Duong, et al.
Published: (2025)
Configuration Defects in Kubernetes
by: Zhang, Yue, et al.
Published: (2025)
by: Zhang, Yue, et al.
Published: (2025)
Defect Prediction Using Stylistic Metrics
by: Yasir, Rafed Muhammad, et al.
Published: (2022)
by: Yasir, Rafed Muhammad, et al.
Published: (2022)
Will It Break in Production? Metric-Driven Prediction of Residual Defects in Python Systems
by: De Rosa, Giuseppe, et al.
Published: (2026)
by: De Rosa, Giuseppe, et al.
Published: (2026)
Contrasting the Hyperparameter Tuning Impact Across Software Defect Prediction Scenarios
by: Rakha, Mohamed Sami, et al.
Published: (2025)
by: Rakha, Mohamed Sami, et al.
Published: (2025)
Context-Adaptive Requirements Defect Prediction through Human-LLM Collaboration
by: Unterbusch, Max, et al.
Published: (2026)
by: Unterbusch, Max, et al.
Published: (2026)
An Empirical Study on JIT Defect Prediction Based on BERT-style Model
by: Guo, Yuxiang, et al.
Published: (2024)
by: Guo, Yuxiang, et al.
Published: (2024)
Managing Human-Centric Software Defects: Insights from GitHub and Practitioners' Perspectives
by: Chauhan, Vedant, et al.
Published: (2024)
by: Chauhan, Vedant, et al.
Published: (2024)
Contextualized Code Pretraining for Code Generation
by: Liu, Chen, et al.
Published: (2026)
by: Liu, Chen, et al.
Published: (2026)
Co-Change Graph Entropy: A New Process Metric for Defect Prediction
by: Hrishikesh, Ethari, et al.
Published: (2025)
by: Hrishikesh, Ethari, et al.
Published: (2025)
Defining and Detecting the Defects of the Large Language Model-based Autonomous Agents
by: Ning, Kaiwen, et al.
Published: (2024)
by: Ning, Kaiwen, et al.
Published: (2024)
Process-based Indicators of Vulnerability Re-Introducing Code Changes: An Exploratory Case Study
by: Shimmi, Samiha, et al.
Published: (2025)
by: Shimmi, Samiha, et al.
Published: (2025)
Back to the Future! Studying Data Cleanness in Defects4J and its Impact on Fault Localization
by: Rafi, Md Nakhla, et al.
Published: (2023)
by: Rafi, Md Nakhla, et al.
Published: (2023)
BDefects4NN: A Backdoor Defect Database for Controlled Localization Studies in Neural Networks
by: Xiao, Yisong, et al.
Published: (2024)
by: Xiao, Yisong, et al.
Published: (2024)
Similar Items
-
ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction?
by: Nam, Doha, et al.
Published: (2025) -
Feature Importance in the Context of Traditional and Just-In-Time Software Defect Prediction Models
by: Haldar, Susmita, et al.
Published: (2024) -
On the calibration of Just-in-time Defect Prediction
by: Shahini, Xhulja, et al.
Published: (2025) -
An Exploratory Study on Just-in-Time Multi-Programming-Language Bug Prediction
by: Li, Zengyang, et al.
Published: (2024) -
IRJIT: A Simple, Online, Information Retrieval Approach for Just-In-Time Software Defect Prediction
by: Sahar, Hareem, et al.
Published: (2022)