Saved in:
| Main Authors: | Dapaah, Emmanuel Charleson, Grabowski, Jens |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.17460 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Quality-Driven Selective Mutation for Deep Learning
by: Ahmed, Zaheed, et al.
Published: (2026)
by: Ahmed, Zaheed, et al.
Published: (2026)
Quality Issues in Machine Learning Software Systems
by: Côté, Pierre-Olivier, et al.
Published: (2023)
by: Côté, Pierre-Olivier, et al.
Published: (2023)
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
by: Rajapaksha, Dilini, et al.
Published: (2021)
by: Rajapaksha, Dilini, et al.
Published: (2021)
When Less is More: On the Value of "Co-training" for Semi-Supervised Software Defect Predictors
by: Majumder, Suvodeep, et al.
Published: (2022)
by: Majumder, Suvodeep, et al.
Published: (2022)
An ML-based Approach to Predicting Software Change Dependencies: Insights from an Empirical Study on OpenStack
by: Arabat, Ali, et al.
Published: (2025)
by: Arabat, Ali, et al.
Published: (2025)
Characterizing Bugs and Quality Attributes in Quantum Software: A Large-Scale Empirical Study
by: Yousuf, Mir Mohammad, et al.
Published: (2025)
by: Yousuf, Mir Mohammad, et al.
Published: (2025)
A Meta-analytical Comparison of Naive Bayes and Random Forest for Software Defect Prediction
by: Awais, Ch Muhammad, et al.
Published: (2023)
by: Awais, Ch Muhammad, et al.
Published: (2023)
Are Latent Vulnerabilities Hidden Gems for Software Vulnerability Prediction? An Empirical Study
by: Le, Triet H. M., et al.
Published: (2024)
by: Le, Triet H. M., et al.
Published: (2024)
An Effective Software Risk Prediction Management Analysis of Data Using Machine Learning and Data Mining Method
by: Xu, Jinxin, et al.
Published: (2024)
by: Xu, Jinxin, et al.
Published: (2024)
Quantum vs. Classical Machine Learning Algorithms for Software Defect Prediction: Challenges and Opportunities
by: Nadim, Md, et al.
Published: (2024)
by: Nadim, Md, et al.
Published: (2024)
Applying Large Language Models to Issue Classification: Revisiting with Extended Data and New Models
by: Aracena, Gabriel, et al.
Published: (2025)
by: Aracena, Gabriel, et al.
Published: (2025)
Studying and Automating Issue Resolution for Software Quality
by: Saha, Antu
Published: (2025)
by: Saha, Antu
Published: (2025)
Software Vulnerability Prediction in Low-Resource Languages: An Empirical Study of CodeBERT and ChatGPT
by: Le, Triet H. M., et al.
Published: (2024)
by: Le, Triet H. M., et al.
Published: (2024)
A Large Scale Survey of Motivation in Software Development and Analysis of its Validity
by: Amit, Idan, et al.
Published: (2024)
by: Amit, Idan, et al.
Published: (2024)
Evaluating the Performance of a D-Wave Quantum Annealing System for Feature Subset Selection in Software Defect Prediction
by: Mandal, Ashis Kumar, et al.
Published: (2024)
by: Mandal, Ashis Kumar, et al.
Published: (2024)
A Large-Scale Study of Model Integration in ML-Enabled Software Systems
by: Sens, Yorick, et al.
Published: (2024)
by: Sens, Yorick, et al.
Published: (2024)
Quality Matters: Evaluating Synthetic Data for Tool-Using LLMs
by: Iskander, Shadi, et al.
Published: (2024)
by: Iskander, Shadi, et al.
Published: (2024)
Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localization
by: Rafi, Md Nakhla, et al.
Published: (2024)
by: Rafi, Md Nakhla, et al.
Published: (2024)
High-Quality Tabular Data Generation using Post-Selected VAE
by: Shulakov, Volodymyr
Published: (2024)
by: Shulakov, Volodymyr
Published: (2024)
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
by: Chaudhari, Shravan, et al.
Published: (2025)
by: Chaudhari, Shravan, et al.
Published: (2025)
An Empirical Study of the Realism of Mutants in Deep Learning
by: Ahmed, Zaheed, et al.
Published: (2025)
by: Ahmed, Zaheed, et al.
Published: (2025)
Assessing the Use of AutoML for Data-Driven Software Engineering
by: Calefato, Fabio, et al.
Published: (2023)
by: Calefato, Fabio, et al.
Published: (2023)
Using Large Language Models to Generate JUnit Tests: An Empirical Study
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
Bridging the Language Gap: An Empirical Study of Bindings for Open Source Machine Learning Libraries Across Software Package Ecosystems
by: Li, Hao, et al.
Published: (2022)
by: Li, Hao, et al.
Published: (2022)
On the calibration of Just-in-time Defect Prediction
by: Shahini, Xhulja, et al.
Published: (2025)
by: Shahini, Xhulja, 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)
Data vs. Model Machine Learning Fairness Testing: An Empirical Study
by: Shome, Arumoy, et al.
Published: (2024)
by: Shome, Arumoy, et al.
Published: (2024)
Automatic Data Labeling for Software Vulnerability Prediction Models: How Far Are We?
by: Le, Triet H. M., et al.
Published: (2024)
by: Le, Triet H. M., et al.
Published: (2024)
SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations
by: Wang, Shuaiqi, et al.
Published: (2026)
by: Wang, Shuaiqi, et al.
Published: (2026)
A Feature-Driven Framework for Software Fault Prediction
by: Ghazi, Ahmad Nauman, et al.
Published: (2026)
by: Ghazi, Ahmad Nauman, et al.
Published: (2026)
SWE-Exp: Experience-Driven Software Issue Resolution
by: Chen, Silin, et al.
Published: (2025)
by: Chen, Silin, et al.
Published: (2025)
Comparative Analysis of Quantum and Classical Support Vector Classifiers for Software Bug Prediction: An Exploratory Study
by: Nadim, Md, et al.
Published: (2025)
by: Nadim, Md, et al.
Published: (2025)
CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance
by: Pai, Kunal, et al.
Published: (2025)
by: Pai, Kunal, et al.
Published: (2025)
FRANC: A Lightweight Framework for High-Quality Code Generation
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
by: Siddiq, Mohammed Latif, et al.
Published: (2023)
Mitigating Data Imbalance for Software Vulnerability Assessment: Does Data Augmentation Help?
by: Le, Triet H. M., et al.
Published: (2024)
by: Le, Triet H. M., et al.
Published: (2024)
Assessing the Quality and Security of AI-Generated Code: A Quantitative Analysis
by: Sabra, Abbas, et al.
Published: (2025)
by: Sabra, Abbas, et al.
Published: (2025)
Large Language Models for Software Engineering: A Reproducibility Crisis
by: Siddiq, Mohammed Latif, et al.
Published: (2025)
by: Siddiq, Mohammed Latif, et al.
Published: (2025)
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
by: Li, Han, et al.
Published: (2025)
by: Li, Han, et al.
Published: (2025)
Better Knowledge Enhancement for Privacy-Preserving Cross-Project Defect Prediction
by: Wang, Yuying, et al.
Published: (2024)
by: Wang, Yuying, et al.
Published: (2024)
Automated Code-centric Software Vulnerability Assessment: How Far Are We? An Empirical Study in C/C++
by: Nguyen, Anh The, et al.
Published: (2024)
by: Nguyen, Anh The, et al.
Published: (2024)
Similar Items
-
Quality-Driven Selective Mutation for Deep Learning
by: Ahmed, Zaheed, et al.
Published: (2026) -
Quality Issues in Machine Learning Software Systems
by: Côté, Pierre-Olivier, et al.
Published: (2023) -
SQAPlanner: Generating Data-Informed Software Quality Improvement Plans
by: Rajapaksha, Dilini, et al.
Published: (2021) -
When Less is More: On the Value of "Co-training" for Semi-Supervised Software Defect Predictors
by: Majumder, Suvodeep, et al.
Published: (2022) -
An ML-based Approach to Predicting Software Change Dependencies: Insights from an Empirical Study on OpenStack
by: Arabat, Ali, et al.
Published: (2025)