Cover Image

LLM Based Input Space Partitioning Testing for Library APIs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Jiageng, Dong, Zhen, Wang, Chong, You, Haozhen, Zhang, Cen, Liu, Yang, Peng, Xin
Format:	Preprint
Published:	2024
Subjects:	Software Engineering Cryptography and Security D.2.5
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ETrace:Event-Driven Vulnerability Detection in Smart Contracts via LLM-Based Trace Analysis
by: Peng, Chenyang, et al.
Published: (2025)

FuzzRDUCC: Fuzzing with Reconstructed Def-Use Chain Coverage
by: Feng, Kai, et al.
Published: (2025)

LSPFuzz: Hunting Bugs in Language Servers
by: Zhu, Hengcheng, et al.
Published: (2025)

Hyperfuzzing: black-box security hypertesting with a grey-box fuzzer
by: Blackwell, Daniel, et al.
Published: (2023)

An Empirical Study of Fuzz Harness Degradation
by: Görz, Philipp, et al.
Published: (2025)

FuzzPilot: Plateau-Triggered Recipe Validation for Structured Text Fuzzing
by: Yao, Zhiyi
Published: (2026)

AddressWatcher: Sanitizer-Based Localization of Memory Leak Fixes
by: Murali, Aniruddhan, et al.
Published: (2024)

LibLMFuzz: LLM-Augmented Fuzz Target Generation for Black-box Libraries
by: Hardgrove, Ian, et al.
Published: (2025)

Evaluating Cryptographic API Misuse Detectors for Go
by: Andersson, Vivi, et al.
Published: (2026)

Detecting Vulnerabilities in Encrypted Software Code while Ensuring Code Privacy
by: Martins, Jorge, et al.
Published: (2025)

A Match Made in Heaven? AI-driven Matching of Vulnerabilities and Security Unit Tests
by: Iannone, Emanuele, et al.
Published: (2025)

Securing Mixed Rust with Hardware Capabilities
by: Yu, Jason Zhijingcheng, et al.
Published: (2025)

Automated Vulnerability Detection Using Deep Learning Technique
by: Yang, Guan-Yan, et al.
Published: (2024)

Control Flow Graph Recovery for Dynamically Loaded Code via Symbolic Library Resolution
by: Mostovyi, Oleksandr
Published: (2026)

Adaptive and AI-Augmented Security Testing: A Systematic Survey of Program Analysis, Feedback-Driven Testing, and Hybrid Learning-Based Approaches
by: Wienczkowski, Michael
Published: (2026)

PinChecker: Identifying Unsound Safe Abstractions of Rust Pinning APIs
by: Dai, Yuxuan, et al.
Published: (2025)

Quantum-Safe Code Auditing: LLM-Assisted Static Analysis and Quantum-Aware Risk Scoring for Post-Quantum Cryptography Migration
by: Shaw, Animesh
Published: (2026)

Security Testing of RESTful APIs With Test Case Mutation
by: Salva, Sebastien, et al.
Published: (2024)

A Comparative Quality Metric for Untargeted Fuzzing with Logic State Coverage
by: Lee, Gwangmu
Published: (2024)

FuzzDistill: Intelligent Fuzzing Target Selection using Compile-Time Analysis and Machine Learning
by: Upadhyay, Saket
Published: (2024)

Automating the Detection of Code Vulnerabilities by Analyzing GitHub Issues
by: Cipollone, Daniele, et al.
Published: (2025)

Refute-or-Promote: An Adversarial Stage-Gated Multi-Agent Review Methodology for High-Precision LLM-Assisted Defect Discovery
by: Agarwal, Abhinav
Published: (2026)

PrediQL: Automated Testing of GraphQL APIs with LLMs
by: Liu, Shaolun, et al.
Published: (2025)

How Effective Are They? Exploring Large Language Model Based Fuzz Driver Generation
by: Zhang, Cen, et al.
Published: (2023)

From Program Slices to Causal Clarity: Evaluating Faithful, Actionable LLM-Generated Failure Explanations via Context Partitioning and LLM-as-a-Judge
by: Porbeck, Julius, et al.
Published: (2026)

Toward Efficient Testing of Graph Neural Networks via Test Input Prioritization
by: Yang, Lichen, et al.
Published: (2025)

Automated Testing of Broken Authentication Vulnerabilities in Web APIs with AuthREST
by: Corradini, Davide, et al.
Published: (2025)

Continuous Discovery of Vulnerabilities in LLM Serving Systems with Fuzzing
by: Zhao, Yunze, et al.
Published: (2026)

Orion: Fuzzing Workflow Automation
by: Bazalii, Max, et al.
Published: (2025)

ClawHub Security Signals: When VirusTotal, Static Analysis, and SkillSpector Disagree
by: Koc, Vincent, et al.
Published: (2026)

PALM: Path-aware LLM-based Test Generation with Comprehension
by: Wu, Yaoxuan, et al.
Published: (2025)

CovRL: Fuzzing JavaScript Engines with Coverage-Guided Reinforcement Learning for LLM-based Mutation
by: Eom, Jueon, et al.
Published: (2024)

Automated Generation of Issue-Reproducing Tests by Combining LLMs and Search-Based Testing
by: Kitsios, Konstantinos, et al.
Published: (2025)

MirrorFuzz: Leveraging LLM and Shared Bugs for Deep Learning Framework APIs Fuzzing
by: Ou, Shiwen, et al.
Published: (2025)

Refining Fuzzed Crashing Inputs for Better Fault Diagnosis
by: Kim, Kieun, et al.
Published: (2025)

ELFuzz: Efficient Input Generation via LLM-driven Synthesis Over Fuzzer Space
by: Chen, Chuyang, et al.
Published: (2025)

Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysis
by: Pei, Changhua, et al.
Published: (2025)

Benchmarking Generative AI Models for Deep Learning Test Input Generation
by: Maryam, et al.
Published: (2024)

Detecting Misuse of Security APIs: A Systematic Review
by: Mousavi, Zahra, et al.
Published: (2023)

E-Test: E'er-Improving Test Suites
by: Qiu, Ketai, et al.
Published: (2025)