Papers software testing
“software testing” 태그가 달린 논문 135편 · 필터 해제
InterEvo-TR: Interactive Evolutionary Test Generation With Readability Assessment
Automated test case generation has proven to be useful to reduce the usually high expenses of software testing. However, several studies have also noted the skepticism of testers regarding the comprehension of generated …
software testingMutation-based Consistency Testing for Evaluating the Code Understanding Capability of LLMs
Large Language Models (LLMs) have shown remarkable capabilities in processing both natural and programming languages, which have enabled various applications in software engineering, such as requirement engineering, code…
Code GenerationHumanEvalsoftware testingIRG: Generating Synthetic Relational Databases using Deep Learning with Insightful Relational Understanding
Synthetic data has numerous applications, including but not limited to software testing at scale, privacy-preserving data sharing to enable smoother collaboration between stakeholders, and data augmentation for analytica…
Data AugmentationGenerative Adversarial NetworkPrivacy Preservingsoftware testing+1A Case Study on Test Case Construction with Large Language Models: Unveiling Practical Insights and Challenges
This paper presents a detailed case study examining the application of Large Language Models (LLMs) in the construction of test cases within the context of software engineering. LLMs, characterized by their advanced natu…
software testingAn empirical study of testing machine learning in the wild
Recently, machine and deep learning (ML/DL) algorithms have been increasingly adopted in many software systems. Due to their inductive nature, ensuring the quality of these systems remains a significant challenge for the…
Autonomous DrivingFairnesssoftware testingCan ChatGPT advance software testing intelligence? An experience report on metamorphic testing
While ChatGPT is a well-known artificial intelligence chatbot being used to answer human's questions, one may want to discover its potential in advancing software testing. We examine the capability of ChatGPT in advancin…
Chatbotsoftware testingTest Case Recommendations with Distributed Representation of Code Syntactic Features
Frequent modifications of unit test cases are inevitable due to software's continuous underlying changes in source code, design, and requirements. Since manually maintaining software test suites is tedious, timely, and c…
software testingReinforcement Learning from Automatic Feedback for High-Quality Unit Test Generation
Software testing is a crucial aspect of software development, and the creation of high-quality tests that adhere to best practices is essential for effective maintenance. Recently, Large Language Models (LLMs) have gaine…
Code Generationreinforcement-learningsoftware testingTestLab: An Intelligent Automated Software Testing Framework
The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity. Consequently, software development is be…
software testingRethinking Diversity in Deep Neural Network Testing
Motivated by the success of traditional software testing, numerous diversity measures have been proposed for testing deep neural networks (DNNs). In this study, we propose a shift in perspective, advocating for the consi…
DiversityDNN Testingsoftware testingValidating Multimedia Content Moderation Software via Semantic Fusion
The exponential growth of social media platforms, such as Facebook and TikTok, has revolutionized communication and content publication in human society. Users on these platforms can publish multimedia content that deliv…
Sentencesoftware testingComparing Software Developers with ChatGPT: An Empirical Investigation
The advent of automation in particular Software Engineering (SE) tasks has transitioned from theory to reality. Numerous scholarly articles have documented the successful application of Artificial Intelligence to address…
ArticlesChatbotFairnessManagement+1Towards Efficient Fine-tuning of Pre-trained Code Models: An Experimental Study and Beyond
Recently, fine-tuning pre-trained code models such as CodeBERT on downstream tasks has achieved great success in many software testing and analysis tasks. While effective and prevalent, fine-tuning the pre-trained parame…
software testingInformation-Theoretic Testing and Debugging of Fairness Defects in Deep Neural Networks
The deep feedforward neural networks (DNNs) are increasingly deployed in socioeconomic critical decision support software systems. DNNs are exceptionally good at finding minimal, sufficient statistical patterns within th…
Decision MakingFairnesssoftware testingConstrained Adversarial Learning for Automated Software Testing: a literature review
It is imperative to safeguard computer applications and information systems against the growing number of cyber-attacks. Automated software testing tools can be developed to quickly analyze many lines of code and detect …
Adversarial Attacksoftware testingTesting the Channels of Convolutional Neural Networks
Neural networks have complex structures, and thus it is hard to understand their inner workings and ensure correctness. To understand and debug convolutional neural networks (CNNs) we propose techniques for testing the c…
channel selectionsoftware testingReasoning-Based Software Testing
With software systems becoming increasingly pervasive and autonomous, our ability to test for their quality is severely challenged. Many systems are called to operate in uncertain and highly-changing environment, not rar…
Causal Discoverysoftware testingGenetic Micro-Programs for Automated Software Testing with Large Path Coverage
Ongoing progress in computational intelligence (CI) has led to an increased desire to apply CI techniques for the purpose of improving software engineering processes, particularly software testing. Existing state-of-the-…
software testingPerfect is the enemy of test oracle
Automation of test oracles is one of the most challenging facets of software testing, but remains comparatively less addressed compared to automated test input generation. Test oracles rely on a ground-truth that can dis…
software testingBoosting Synthetic Data Generation with Effective Nonlinear Causal Discovery
Synthetic data generation has been widely adopted in software testing, data privacy, imbalanced learning, and artificial intelligence explanation. In all such contexts, it is crucial to generate plausible data samples. A…
Causal Discoverysoftware testingSynthetic Data Generation