Papers software testing
“software testing” 태그가 달린 논문 135편 · 필터 해제
Navigating the growing field of research on AI for software testing -- the taxonomy for AI-augmented software testing and an ontology-driven literature survey
In industry, software testing is the primary method to verify and validate the functionality, performance, security, usability, and so on, of software-based systems. Test automation has gained increasing attention in ind…
software testingGuaranteed Guess: A Language Modeling Approach for CISC-to-RISC Transpilation with Testing Guarantees
The hardware ecosystem is rapidly evolving, with increasing interest in translating low-level programs across different instruction set architectures (ISAs) in a quick, flexible, and correct way to enhance the portabilit…
Code TranslationHumanEvalLanguage ModelingLanguage Modelling+2IntenTest: Stress Testing for Intent Integrity in API-Calling LLM Agents
LLM agents are increasingly deployed to automate real-world tasks by invoking APIs through natural language instructions. While powerful, they often suffer from misinterpretation of user intent, leading to the agent's ac…
software testingThe Impact of Software Testing with Quantum Optimization Meets Machine Learning
Modern software systems complexity challenges efficient testing, as traditional machine learning (ML) struggles with large test suites. This research presents a hybrid framework integrating Quantum Annealing with ML to o…
Defect Detectionsoftware testingEvoGPT: Enhancing Test Suite Robustness via LLM-Based Generation and Genetic Optimization
Large Language Models (LLMs) have recently emerged as promising tools for automated unit test generation. We introduce a hybrid framework called EvoGPT that integrates LLM-based test generation with evolutionary search t…
DiversityFault Detectionsoftware testingOn the Need for a Statistical Foundation in Scenario-Based Testing of Autonomous Vehicles
Scenario-based testing has emerged as a common method for autonomous vehicles (AVs) safety, offering a more efficient alternative to mile-based testing by focusing on high-risk scenarios. However, fundamental questions p…
Autonomous Vehiclessoftware testingAutomated Unit Test Case Generation: A Systematic Literature Review
Software is omnipresent within all factors of society. It is thus important to ensure that software are well tested to mitigate bad user experiences as well as the potential for severe financial and human losses. Softwar…
software testingSystematic Literature ReviewTest It Before You Trust It: Applying Software Testing for Trustworthy In-context Learning
In-context learning (ICL) has emerged as a powerful capability of large language models (LLMs), enabling them to perform new tasks based on a few provided examples without explicit fine-tuning. Despite their impressive a…
In-Context LearningPhilosophyQuestion AnsweringSentiment Analysis+1Harden and Catch for Just-in-Time Assured LLM-Based Software Testing: Open Research Challenges
Despite decades of research and practice in automated software testing, several fundamental concepts remain ill-defined and under-explored, yet offer enormous potential real-world impact. We show that these concepts rais…
software testingExpectations vs Reality -- A Secondary Study on AI Adoption in Software Testing
In the software industry, artificial intelligence (AI) has been utilized more and more in software development activities. In some activities, such as coding, AI has already been an everyday tool, but in software testing…
software testingFrom Code Generation to Software Testing: AI Copilot with Context-Based RAG
The rapid pace of large-scale software development places increasing demands on traditional testing methodologies, often leading to bottlenecks in efficiency, accuracy, and coverage. We propose a novel perspective on sof…
ChatbotCode GenerationRAGRetrieval-augmented Generation+1Towards Trustworthy GUI Agents: A Survey
GUI agents, powered by large foundation models, can interact with digital interfaces, enabling various applications in web automation, mobile navigation, and software testing. However, their increasing autonomy has raise…
Decision MakingSequential Decision Makingsoftware testingSurveyIntegrating Artificial Intelligence with Human Expertise: An In-depth Analysis of ChatGPT's Capabilities in Generating Metamorphic Relations
Context: This paper provides an in-depth examination of the generation and evaluation of Metamorphic Relations (MRs) using GPT models developed by OpenAI, with a particular focus on the capabilities of GPT-4 in software …
software testingVulnerability Detection: From Formal Verification to Large Language Models and Hybrid Approaches: A Comprehensive Overview
Software testing and verification are critical for ensuring the reliability and security of modern software systems. Traditionally, formal verification techniques, such as model checking and theorem proving, have provide…
Automated Theorem Provingsoftware testingVulnerability DetectionRule-Guided Reinforcement Learning Policy Evaluation and Improvement
We consider the challenging problem of using domain knowledge to improve deep reinforcement learning policies. To this end, we propose LEGIBLE, a novel approach, following a multi-step process, which starts by mining rul…
Deep Reinforcement Learningreinforcement-learningReinforcement Learningsoftware testingToolFuzz -- Automated Agent Tool Testing
Large Language Model (LLM) Agents leverage the advanced reasoning capabilities of LLMs in real-world applications. To interface with an environment, these agents often rely on tools, such as web search or database APIs. …
Large Language ModelPrompt Engineeringsoftware testingWIP: Assessing the Effectiveness of ChatGPT in Preparatory Testing Activities
This innovative practice WIP paper describes a research study that explores the integration of ChatGPT into the software testing curriculum and evaluates its effectiveness compared to human-generated testing artifacts. I…
software testingTowards Reliable LLM-Driven Fuzz Testing: Vision and Road Ahead
Fuzz testing is a crucial component of software security assessment, yet its effectiveness heavily relies on valid fuzz drivers and diverse seed inputs. Recent advancements in Large Language Models (LLMs) offer transform…
software testingvalidCLOVER: A Test Case Generation Benchmark with Coverage, Long-Context, and Verification
Software testing is a critical aspect of software development, yet generating test cases remains a routine task for engineers. This paper presents a benchmark, CLOVER, to evaluate models' capabilities in generating and c…
16k4ksoftware testingIdentifying Flaky Tests in Quantum Code: A Machine Learning Approach
Testing and debugging quantum software pose significant challenges due to the inherent complexities of quantum mechanics, such as superposition and entanglement. One challenge is indeterminacy, a fundamental characterist…
software testing