Cover Image

Constrained Adversarial Learning for Automated Software Testing: a literature review

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Vitorino, João, Dias, Tiago, Fonseca, Tiago, Maia, Eva, Praça, Isabel
Format:	Preprint
Published:	2023
Subjects:	Software Engineering Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer
by: Dias, Tiago, et al.
Published: (2024)

SCoPE: Evaluating LLMs for Software Vulnerability Detection
by: Gonçalves, José, et al.
Published: (2024)

Evaluating LLaMA 3.2 for Software Vulnerability Detection
by: Gonçalves, José, et al.
Published: (2025)

Enhancing Large Language Models with Faster Code Preprocessing for Vulnerability Detection
by: Gonçalves, José, et al.
Published: (2025)

Adversarial Evasion Attack Efficiency against Large Language Models
by: Vitorino, João, et al.
Published: (2024)

SoK: Realistic Adversarial Attacks and Defenses for Intelligent Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2023)

Automated Trustworthiness Testing for Machine Learning Classifiers
by: Cho, Steven, et al.
Published: (2024)

A systematic literature Review for Transformer-based Software Vulnerability detection
by: Naseer, Fiza, et al.
Published: (2026)

An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection
by: Vitorino, João, et al.
Published: (2024)

Learning-Based Testing for Deep Learning: Enhancing Model Robustness with Adversarial Input Prioritization
by: Rahman, Sheikh Md Mushfiqur, et al.
Published: (2025)

From Data to Action: Exploring AI and IoT-driven Solutions for Smarter Cities
by: Dias, Tiago, et al.
Published: (2023)

Reliable Feature Selection for Adversarially Robust Cyber-Attack Detection
by: Vitorino, João, et al.
Published: (2024)

Evaluating Local Explainability Metrics for Machine Learning Models on Tabular Data
by: Pereira, Tomás, et al.
Published: (2026)

Cataloguing Hugging Face Models to Software Engineering Activities: Automation and Findings
by: González, Alexandra, et al.
Published: (2025)

CA2: Code-Aware Agent for Automated Game Testing
by: Adaikkappan, Valliappan Chidambaram, et al.
Published: (2026)

Automating REST API Postman Test Cases Using LLM
by: Sri, S Deepika, et al.
Published: (2024)

PrismaDV: Automated Task-Aware Data Unit Test Generation
by: Chen, Hao, et al.
Published: (2026)

Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics
by: Tran, Khang, et al.
Published: (2026)

The Impact of Software Testing with Quantum Optimization Meets Machine Learning
by: Bandarupalli, Gopichand
Published: (2025)

Machine Learning Transferability for Malware Detection
by: Vieira, César, et al.
Published: (2026)

What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims
by: Jones, Jason, et al.
Published: (2024)

SmartChoices: Augmenting Software with Learned Implementations
by: Golovin, Daniel, et al.
Published: (2023)

Applications and Challenges of Fairness APIs in Machine Learning Software
by: Das, Ajoy, et al.
Published: (2025)

Investigating Reproducibility in Deep Learning-Based Software Fault Prediction
by: Mukhtar, Adil, et al.
Published: (2024)

Network Simulation with Complex Cyber-attack Scenarios
by: Dias, Tiago, et al.
Published: (2024)

A Systematic Literature Review on the Use of Machine Learning in Software Engineering
by: Fred, Nyaga, et al.
Published: (2024)

Improving the Reproducibility of Deep Learning Software: An Initial Investigation through a Case Study Analysis
by: Ravi, Nikita, et al.
Published: (2025)

Automating Formal Verification with Reinforcement Learning and Recursive Inference
by: Tan, Max
Published: (2026)

Automated Modernization of Machine Learning Engineering Notebooks for Reproducibility
by: Jin, Bihui, et al.
Published: (2026)

Bug Severity Prediction in Software Projects Using Supervised Machine Learning Models
by: Nice, Nafisha Tamanna
Published: (2026)

More Rigorous Software Engineering Would Improve Reproducibility in Machine Learning Research
by: Wolter, Moritz, et al.
Published: (2025)

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

SPATA: Systematic Pattern Analysis for Detailed and Transparent Data Cards
by: Vitorino, João, et al.
Published: (2025)

Targeted Deep Learning System Boundary Testing
by: Weißl, Oliver, et al.
Published: (2024)

Perspective of Software Engineering Researchers on Machine Learning Practices Regarding Research, Review, and Education
by: Mojica-Hanke, Anamaria, et al.
Published: (2024)

Quantum vs. Classical Machine Learning Algorithms for Software Defect Prediction: Challenges and Opportunities
by: Nadim, Md, et al.
Published: (2024)

Automating the Training and Deployment of Models in MLOps by Integrating Systems with Machine Learning
by: Liang, Penghao, et al.
Published: (2024)

Should Code Models Learn Pedagogically? A Preliminary Evaluation of Curriculum Learning for Real-World Software Engineering Tasks
by: Khant, Kyi Shin, et al.
Published: (2025)

Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software
by: Chen, Zhenpeng, et al.
Published: (2024)

R-LAM: Reproducibility-Constrained Large Action Models for Scientific Workflow Automation
by: Sureshkumar, Suriya
Published: (2026)