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software testing

Papers

Showing 1–50 of 135 papers

TitleStatusHype
Guaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees—0
Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature surveyCode0
IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents—0
The Impact of Software Testing with Quantum Optimization Meets Machine Learning—0
EvoGPT: Enhancing Test Suite Robustness via LLM-Based Generation and Genetic Optimization—0
On the Need for a Statistical Foundation in Scenario-Based Testing of Autonomous Vehicles—0
Automated Unit Test Case Generation: A Systematic Literature Review—0
Test It Before You Trust It: Applying Software Testing for Trustworthy In-context LearningCode0
Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges—0
Expectations vs Reality -- A Secondary Study on AI Adoption in Software Testing—0
From Code Generation to Software Testing: AI Copilot with Context-Based RAG—0
Towards Trustworthy GUI Agents: A SurveyCode0
Integrating Artificial Intelligence with Human Expertise: An In-depth Analysis of ChatGPT's Capabilities in Generating Metamorphic Relations—0
Vulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview—0
Rule-Guided Reinforcement Learning Policy Evaluation and Improvement—0
ToolFuzz -- Automated Agent Tool Testing—0
WIP: Assessing the Effectiveness of ChatGPT in Preparatory Testing Activities—0
Towards Reliable LLM-Driven Fuzz Testing: Vision and Road Ahead—0
CLOVER: A Test Case Generation Benchmark with Coverage, Long-Context, and Verification—0
Identifying Flaky Tests in Quantum Code: A Machine Learning Approach—0
A Systematic Approach for Assessing Large Language Models' Test Case Generation Capability—0
Assessing Data Augmentation-Induced Bias in Training and Testing of Machine Learning ModelsCode0
Toward Neurosymbolic Program Comprehension—0
Many-Objective Neuroevolution for Testing Games—0
An efficient approach to represent enterprise web application structure using Large Language Model in the service of Intelligent Quality Engineering—0
The Potential of LLMs in Automating Software Testing: From Generation to Reporting—0
Reinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation—0
Design choices made by LLM-based test generators prevent them from finding bugs—0
CPP-UT-Bench: Can LLMs Write Complex Unit Tests in C++?—0
Software testing for project report.—0
VALTEST: Automated Validation of Language Model Generated Test Cases—0
Can Search-Based Testing with Pareto Optimization Effectively Cover Failure-Revealing Test Inputs?Code0
TAEGAN: Generating Synthetic Tabular Data For Data Augmentation—0
On the Effectiveness of LLMs for Manual Test Verifications—0
Computer Vision Intelligence Test Modeling and Generation: A Case Study on Smart OCR—0
Exploring the Integration of Large Language Models in Industrial Test Maintenance Processes—0
The Future of Software Testing: AI-Powered Test Case Generation and Validation—0
The Role of Artificial Intelligence and Machine Learning in Software Testing—0
Testing and Evaluation of Large Language Models: Correctness, Non-Toxicity, and Fairness—0
Leveraging Large Language Models for Enhancing the Understandability of Generated Unit TestsCode1
A System for Automated Unit Test Generation Using Large Language Models and Assessment of Generated Test Suites—0
MAO: A Framework for Process Model Generation with Multi-Agent Orchestration—0
FuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer—0
SWT-Bench: Testing and Validating Real-World Bug-Fixes with Code AgentsCode2
Data Augmentation by Fuzzing for Neural Test Generation—0
BugBlitz-AI: An Intelligent QA Assistant—0
Artificial intelligence for context-aware visual change detection in software test automation—0
Fuzzy Inference System for Test Case Prioritization in Software Testing—0
LLM-Powered Test Case Generation for Detecting Bugs in Plausible ProgramsCode0
Tasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches—0
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