دانلود کتاب تست کامل پشته، ویرایش دوم راهنمای عملی برای ارائه نرم‌افزار با کیفیت بالا در عصر هوش مصنوعی

If you’re in the software industry, it is highly likely that you have worn the testing hat at least once, irrespective of your role. That’s because testing is such an integral aspect of software engineering, woven into every stage of the software delivery cycle. Especially in today’s context, where AI coding tools churn code at a rapid pace, testing for quality has become more crucial than ever before. Testing, like other software disciplines, has evolved to incorporate new practices, frameworks, methodologies, and tools over the years. Manual testing has evolved into manual exploratory testing, while the rise of automated testing combined with continuous integration and continuous delivery (CI/CD) practices has greatly increased the value derived from testing. Today, agentic AI tools claim to speed both manual and automated testing by 70% to 80%. When moving beyond functional use cases, manual and automated testing of cross-functional requirements such as performance, security, reliability, and accessibility ensures holistic feedback on quality and allows you to continuously deliver high-quality software. This is why full stack testing is a desirable specialization in the industry. With AI testing agents offering to automate tasks across both functional and cross-functional requirement testing, this holistic full stack testing knowledge, including how to architect and orchestrate the AI testing agent, becomes the need of the hour. I presume you’re here because you want to transpile into a full stack tester so you can deliver high-quality software at work. First, kudos on your commitment; second, welcome aboard!