Papers software testing
“software testing” 태그가 달린 논문 135편 · 필터 해제
A System for Automated Unit Test Generation Using Large Language Models and Assessment of Generated Test Suites
Unit tests represent the most basic level of testing within the software testing lifecycle and are crucial to ensuring software correctness. Designing and creating unit tests is a costly and labor-intensive process that …
Code Generationsoftware testingMAO: A Framework for Process Model Generation with Multi-Agent Orchestration
Process models are frequently used in software engineering to describe business requirements, guide software testing and control system improvement. However, traditional process modeling methods often require the partici…
Hallucinationsoftware testingFuzzTheREST: An Intelligent Automated Black-box RESTful API Fuzzer
Software's pervasive impact and increasing reliance in the era of digital transformation raise concerns about vulnerabilities, emphasizing the need for software security. Fuzzy testing is a dynamic analysis software test…
Reinforcement Learning (RL)software testingVulnerability DetectionSWT-Bench: Testing and Validating Real-World Bug-Fixes with Code Agents
Rigorous software testing is crucial for developing and maintaining high-quality code, making automated test generation a promising avenue for both improving software quality and boosting the effectiveness of code genera…
Code GenerationCode Repairsoftware testingData Augmentation by Fuzzing for Neural Test Generation
Testing is essential to modern software engineering for building reliable software. Given the high costs of manually creating test cases, automated test case generation, particularly methods utilizing large language mode…
Code GenerationData AugmentationDiversitysoftware testing+1BugBlitz-AI: An Intelligent QA Assistant
The evolution of software testing from manual to automated methods has significantly influenced quality assurance (QA) practices. However, challenges persist in post-execution phases, particularly in result analysis and …
software testingArtificial intelligence for context-aware visual change detection in software test automation
Automated software testing is integral to the software development process, streamlining workflows and ensuring product reliability. Visual testing within this context, especially concerning user interface (UI) and user …
Change Detectionsoftware testingFuzzy Inference System for Test Case Prioritization in Software Testing
In the realm of software development, testing is crucial for ensuring software quality and adherence to requirements. However, it can be time-consuming and resource-intensive, especially when dealing with large and compl…
software testingLLM-Powered Test Case Generation for Detecting Bugs in Plausible Programs
Detecting tricky bugs in plausible programs, those that pass existing test suites yet still contain bugs, remains a significant challenge in software testing. To address this problem, we propose TrickCatcher, an LLM-powe…
software testingTasks People Prompt: A Taxonomy of LLM Downstream Tasks in Software Verification and Falsification Approaches
Prompting has become one of the main approaches to leverage emergent capabilities of Large Language Models [Brown et al. NeurIPS 2020, Wei et al. TMLR 2022, Wei et al. NeurIPS 2022]. Recently, researchers and practitione…
ArticlesFault localizationIn-Context Learningsoftware testing+1Machine Learning Robustness: A Primer
This chapter explores the foundational concept of robustness in Machine Learning (ML) and its integral role in establishing trustworthiness in Artificial Intelligence (AI) systems. The discussion begins with a detailed d…
software testingTransfer LearningCoverUp: Effective High Coverage Test Generation for Python
Testing is an essential part of software development. Test generation tools attempt to automate the otherwise labor-intensive task of test creation, but generating high-coverage tests remains challenging. This paper prop…
software testingComprehensive Evaluation and Insights into the Use of Large Language Models in the Automation of Behavior-Driven Development Acceptance Test Formulation
Behavior-driven development (BDD) is an Agile testing methodology fostering collaboration among developers, QA analysts, and stakeholders. In this manuscript, we propose a novel approach to enhance BDD practices using la…
Few-Shot LearningIn-Context LearningLarge Language ModelPrompt Engineering+4Towards Principled Representation Learning from Videos for Reinforcement Learning
We study pre-training representations for decision-making using video data, which is abundantly available for tasks such as game agents and software testing. Even though significant empirical advances have been made on t…
Contrastive Learningreinforcement-learningReinforcement LearningRepresentation Learning+1RITFIS: Robust input testing framework for LLMs-based intelligent software
The dependence of Natural Language Processing (NLP) intelligent software on Large Language Models (LLMs) is increasingly prominent, underscoring the necessity for robustness testing. Current testing methods focus solely …
Combinatorial Optimizationsoftware testingQuanTest: Entanglement-Guided Testing of Quantum Neural Network Systems
Quantum Neural Network (QNN) combines the Deep Learning (DL) principle with the fundamental theory of quantum mechanics to achieve machine learning tasks with quantum acceleration. Recently, QNN systems have been found t…
software testingUniTSyn: A Large-Scale Dataset Capable of Enhancing the Prowess of Large Language Models for Program Testing
The remarkable capability of large language models (LLMs) in generating high-quality code has drawn increasing attention in the software testing community. However, existing code LLMs often demonstrate unsatisfactory cap…
software testingOn the Challenges of Fuzzing Techniques via Large Language Models
In the modern era where software plays a pivotal role, software security and vulnerability analysis are essential for secure software development. Fuzzing test, as an efficient and traditional software testing method, ha…
software testingSurveyGenerative AI to Generate Test Data Generators
Generating fake data is an essential dimension of modern software testing, as demonstrated by the number and significance of data faking libraries. Yet, developers of faking libraries cannot keep up with the wide range o…
software testingCode-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM
Testing plays a pivotal role in ensuring software quality, yet conventional Search Based Software Testing (SBST) methods often struggle with complex software units, achieving suboptimal test coverage. Recent works using …
software testing