Testing Is All About Principles
Explore key principles for writing effective and confidence-boosting tests in React applications, focusing on programming fundamentals rather than specific tools or libraries.
Fearless Browser Testing
Discover browser test automation techniques to streamline development, improve code quality, and enhance performance across multiple browsers without manual testing or VMs.
The Browser Hackers Guide to Instantly Loading Everything
Explore browser optimization techniques for instant loading, including preload, prefetch, HTTP/2 Server Push, and efficient JavaScript bundling, to enhance user experience on mobile devices.
QEMU-Native Hooking Bridge for Binary Fuzzing
Explore advanced binary fuzzing techniques through QEMU-Native Hooking Bridge, offering improved instruction hooking and memory control for efficient vulnerability detection in compiled code without source access.
Source-Based Code Coverage of Linux Kernel
Explore source-based code coverage techniques for the Linux kernel, enhancing testing and development practices for improved kernel reliability.
Accelerating Fuzzing through Prefix-Guided Execution
Explore prefix-guided execution for accelerating coverage-guided fuzzing, improving bug detection and code coverage in software testing through early termination of unlikely tests.
How We Almost Secured Our Project by Writing More Tests
Explore how increased testing nearly secured a project, delving into code coverage, seccomp profiles, and syscall extraction. Learn about Harpoon and the benefits of libbpfgo in Golang development.
Instrumenting the Wolfram Language - Profiling, Coverage and Debugging
Automate code instrumentation for profiling, coverage reporting, and debugging in Wolfram Language using the new CodeTools package.
Test Java and C Applications with Python
Scopri come utilizzare Python per testare codice Java e C, riducendo i tempi di sviluppo e migliorando la copertura dei test per applicazioni legacy e servizi di rete.
Near Zero-Overhead Python Code Coverage - SlipCover Introduction
Discover SlipCover, a new tool reducing Python code coverage overhead to 5%. Learn its advantages over coverage.py and integration with Python 3.12's Low Impact Monitoring API.
Near Zero-Overhead Python Code Coverage - SlipCover
Discover SlipCover, a new tool reducing Python code coverage overhead to 5%. Learn its advantages over coverage.py and integration with Python 3.12's Low Impact Monitoring API.
What You Can Learn from an Open-Source Project with 250 Million Downloads
Insights from managing a popular open-source library: tools, techniques, and best practices for high-quality development, testing, and maintenance of widely-used software projects.
Zen and the Art of Code Life Cycle Maintenance
Explore software quality through tests, types, and analysis, drawing parallels to "Zen and the Art of Motorcycle Maintenance" to uncover key aspects and their interplay.
Game Changing Advances in Windows Shellcode Analysis Using SHAREM Framework
Discover groundbreaking advances in Windows shellcode analysis through SHAREM framework, offering enhanced emulation, complete code coverage, and superior disassembly capabilities for security professionals.
The State of Code Coverage for Kotlin
Explore Kotlin code coverage tools, techniques, and challenges. Learn to interpret results and understand future improvements for effective testing.
Ways to Realistically Prioritize Code Quality for Engineering Teams
Explore strategies for prioritizing code quality in engineering teams, focusing on communication, incentives, and practical techniques for busy developers.
Streamlining Testing in a Large Python Codebase
Optimize Python testing in large codebases using parallel execution, efficient startup, and targeted coverage reporting. Boost development speed and code quality with practical strategies and open-source tools.
Quality Matters in Ansible Automation - AnsibleFest 2019
Explore ansible-test for quality assurance in Ansible development. Learn sanity, integration, and unit testing techniques to enhance your automation workflows.
Who Needs C++ Unit Tests Anyway? - Modernizing Legacy Code with 0% Code Coverage - 2024
Explore practical strategies for confidently modernizing large legacy C++ codebases without existing tests. Learn actionable approaches to understand, future-proof, and update code to new language standards.
Measuring Code Coverage of the Linux Kernel in Accordance with RTCA DO-178C
Explore Boeing's approach to measuring Linux kernel code coverage for safety-critical avionics, focusing on RTCA DO-178C requirements and the enhancement of LLVM coverage tools.
Roslyn Source Generators - Never Send a Human to Do a Machine's Job
Explore .NET Source Generators: automate implementations, replace Reflection with high-performance solutions, and learn advanced topics like testing, benchmarking, and tools for efficient metaprogramming in C#.