Latest Articles for Software Testing

A focused approach to quickly identify software bugs through targeted testing.

A study on testing controller systems for the E-puck educational robot.

Learn how industry professionals define and assess test-case quality.

A study on improving cancer data testing efficiency using machine learning.

Improving test data generation for aircraft systems using automation techniques.

A new method enhances the detection of logic bugs in XML processing tools.

A new tool evaluates Syzbot's ability to find Linux kernel bugs.

A novel approach to software testing using gray-box fuzzing and gradient descent.

New methods improve efficiency in automata learning for complex systems.

Instiller improves CPU fuzz testing with efficient techniques and better bug detection.

MobFuzz enhances fuzz testing with multi-objective optimization for better software security.

A look into model-based testing methods for system verification.

Introducing FormNexus, a method for automating web form testing efficiently.

A dataset to enhance the accuracy of unit test generation using large language models.

Research highlights the importance of user-focused software design in fixing defects.

A new fuzzer enhances bug detection in LLVM's complex codebase.

RESTSpecIT automates the process of documenting and testing RESTful APIs effectively.

This study analyzes common mistakes made by beginners in Alloy software modeling.

A model to evaluate test case and suite quality for better software reliability.

A novel approach using language models to test medical rule engines improves accuracy.

Exploring how QELM improves elevator performance and waiting time predictions.

Using advanced AI to find and fix Android app compatibility issues.

Learn how execution taints and memoization can enhance mutation analysis efficiency.

Investigating techniques to enhance security in BusyBox used in IoT devices.

Improving fuzz testing of embedded systems by enhancing MMIO models.

A new automated approach to enhance UAV software testing using AI.

New approaches to enhance clarity and reduce issues in software requirements.

A study on how Large Language Models can improve vulnerability detection in software.

This study assesses large language models for generating text inputs in mobile applications.

A look at using language models to evaluate software requirements satisfaction.

An overview of testing methods for deep learning libraries and their significance.

Delm enhances app testing efficiency using deep links for better coverage and reliability.

This study examines the role of LLMs in creating effective test oracles for software.

Introducing Themis, an automated tool for fault detection in deep learning systems.

This article discusses the need for better evaluation practices in fuzzing research.

Learn how LLMs enhance the efficiency of web-form testing.

A look into the security challenges and solutions for hardware in the cloud.

Learn about fuzzing techniques to enhance web application security.

Using language models to improve software bug detection and testing efficiency.

Testing LLMs is essential for safe and effective AI applications.