Cover Image

Leveraging Data Characteristics for Bug Localization in Deep Learning Programs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Manke, Ruchira, Wardat, Mohammad, Khomh, Foutse, Rajan, Hridesh
Format:	Preprint
Published:	2024
Subjects:	Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mock Deep Testing: Toward Separate Development of Data and Models for Deep Learning
by: Manke, Ruchira, et al.
Published: (2025)

Towards Understanding the Impact of Data Bugs on Deep Learning Models in Software Engineering
by: Shah, Mehil B, et al.
Published: (2024)

Imitation Game: Reproducing Deep Learning Bugs Leveraging an Intelligent Agent
by: Shah, Mehil B, et al.
Published: (2025)

Towards Enhancing the Reproducibility of Deep Learning Bugs: An Empirical Study
by: Shah, Mehil B., et al.
Published: (2024)

muPRL: A Mutation Testing Pipeline for Deep Reinforcement Learning based on Real Faults
by: Thomas, Deepak-George, et al.
Published: (2024)

Fault Localization in Deep Learning-based Software: A System-level Approach
by: Morovati, Mohammad Mehdi, et al.
Published: (2024)

Continuously Learning Bug Locations
by: Mindom, Paulina Stevia Nouwou, et al.
Published: (2024)

Inferring Data Preconditions from Deep Learning Models for Trustworthy Prediction in Deployment
by: Ahmed, Shibbir, et al.
Published: (2024)

GIST: Generated Inputs Sets Transferability in Deep Learning
by: Tambon, Florian, et al.
Published: (2023)

SelfHeal: Empirical Fix Pattern Analysis and Bug Repair in LLM Agents
by: Islam, Niful, et al.
Published: (2026)

A Survey of Bugs in AI-Generated Code
by: Gao, Ruofan, et al.
Published: (2025)

Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study
by: Morovati, Mohammad Mehdi, et al.
Published: (2023)

Real Faults in Model Context Protocol (MCP) Software: a Comprehensive Taxonomy
by: Taraghi, Mina, et al.
Published: (2026)

Mitigating False Positives in Static Memory Safety Analysis of Rust Programs via Reinforcement Learning
by: P, Akilesh, et al.
Published: (2026)

PathOCL: Path-Based Prompt Augmentation for OCL Generation with GPT-4
by: Abukhalaf, Seif, et al.
Published: (2024)

SDLog: A Deep Learning Framework for Detecting Sensitive Information in Software Logs
by: Aghili, Roozbeh, et al.
Published: (2025)

Protecting Privacy in Software Logs: What Should Be Anonymized?
by: Aghili, Roozbeh, et al.
Published: (2024)

Machine Learning Robustness: A Primer
by: Braiek, Houssem Ben, et al.
Published: (2024)

Data-Driven Evidence-Based Syntactic Sugar Design
by: OBrien, David, et al.
Published: (2024)

Bugs in Large Language Models Generated Code: An Empirical Study
by: Tambon, Florian, et al.
Published: (2024)

When Agents Fail: A Comprehensive Study of Bugs in LLM Agents with Automated Labeling
by: Islam, Niful, et al.
Published: (2026)

Characterizing Faults in Agentic AI: A Taxonomy of Types, Symptoms, and Root Causes
by: Shah, Mehil B, et al.
Published: (2026)

Towards Understanding the Challenges of Bug Localization in Deep Learning Systems
by: Jahan, Sigma, et al.
Published: (2024)

An Empirical Study of Self-Admitted Technical Debt in Machine Learning Software
by: Bhatia, Aaditya, et al.
Published: (2023)

FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks
by: Openja, Moses, et al.
Published: (2025)

Improving the Robustness of Large Language Models for Code Tasks via Fine-tuning with Perturbed Data
by: Liu, Yang, et al.
Published: (2026)

Trained Without My Consent: Detecting Code Inclusion In Language Models Trained on Code
by: Majdinasab, Vahid, et al.
Published: (2024)

On the Effectiveness of Log Representation for Log-based Anomaly Detection
by: Wu, Xingfang, et al.
Published: (2023)

RefAgent: A Multi-agent LLM-based Framework for Automatic Software Refactoring
by: Oueslati, Khouloud, et al.
Published: (2025)

Dynasto: Validity-Aware Dynamic-Static Parameter Optimization for Autonomous Driving Testing
by: Humeniuk, Dmytro, et al.
Published: (2026)

Understanding Web Application Workloads and Their Applications: Systematic Literature Review and Characterization
by: Aghili, Roozbeh, et al.
Published: (2024)

Adversarial Attack Classification and Robustness Testing for Large Language Models for Code
by: Liu, Yang, et al.
Published: (2025)

Reputation Gaming in Stack Overflow
by: Mazloomzadeh, Iren, et al.
Published: (2021)

Toward Debugging Deep Reinforcement Learning Programs with RLExplorer
by: Bouchoucha, Rached, et al.
Published: (2024)

IRepair: An Intent-Aware Approach to Repair Data-Driven Errors in Large Language Models
by: Imtiaz, Sayem Mohammad, et al.
Published: (2025)

Exploring Security Practices in Infrastructure as Code: An Empirical Study
by: Verdet, Alexandre, et al.
Published: (2023)

From Technical Excellence to Practical Adoption: Lessons Learned Building an ML-Enhanced Trace Analysis Tool
by: Shahedi, Kaveh, et al.
Published: (2025)

Performance Smells in ML and Non-ML Python Projects: A Comparative Study
by: Belias, François, et al.
Published: (2025)

LLMs and Stack Overflow Discussions: Reliability, Impact, and Challenges
by: Da Silva, Leuson, et al.
Published: (2024)

Tracing Optimization for Performance Modeling and Regression Detection
by: Shahedi, Kaveh, et al.
Published: (2024)