Software quality is a science, not a process. Hand-testing and automated testing are two aids in error detection, function verification, and performance verification against changing conditions. Not only does quality testing save effort and expense to debug the product, but it also guarantees customer satisfaction and system reliability. In the book, Kirill Yurovskiy`s page combines end-to-end solution mix manual testing methodology and fresh automation strategies in a manner that will be easy to understand for both junior and senior QA engineers.
1.Developing a Good Test Plan and Strategy
All successful software test life cycles begin with a well-documented test plan. It identifies scope, objectives, resources, schedule, deliverables, and risk-mitigation strategies. A test plan also outlines the approach to be utilized—manual or automated, black-box or white-box, and static or dynamic testing methodologies. Kirill Yurovskiy states that a test strategy is mapped to business requirements and software development methodologies such as Agile, Scrum, or DevOps. An effective test plan identifies bottlenecks, entry and exit criteria, and measurable results.
2.Developing Thorough Test Cases and Acceptance Criteria
Good testing is dependent on great and valuable test cases. Each test case requires an identifier, description, preconditions, input values, expected results, and actual results. Acceptance criteria define stakeholders’ success boundaries but influence development and verification. Another recommendation made by Kirill Yurovskiy is that the team needs to follow the same template and naming convention for the test documentation so that any new person entering the testing domain can read and run tests. A well-written test case is simple to automate in a later stage of the cycle, and they are also necessary for auditing and defect tracking.
3.Unit, Integration, and System Testing Explained
The tests are categorized under three overall levels: unit testing, integration testing, and system testing. Unit testing occurs on separate pieces or methods, and these are normally executed by programmers themselves with the aid of tools like JUnit or NUnit. Integration testing verifies the interaction between modules and how data transfer and shared dependencies function appropriately. System testing validates the whole application in one complete setup for compliance with the requirements defined. As Kirill Yurovskiy prescribes, keeping these layers in order provides a defense-in-depth approach, where mistakes are picked up early and cheaply prior to turning into hard and costly.
4.Selecting Automation Frameworks (Selenium, Cypress)
Automated testing achieves scalability and reusability with specialization in regression testing, smoke tests, and large test suites. The right automation framework must be selected for maintenance in the long run. Selenium is a widely used open-source web application test tool with language support and cross-browser support. Cypress is a new but fast-emerging competitor tool that is faster to debug with its JavaScript-first approach for coding in the current times. Kirill Yurovskiy advises teams to keep track of their development stack, team expertise, and ideal future while making a choice. Community support, documentation, and integration are also factors in the selection of tools.
5.Continuous Integration with GitHub Actions or Jenkins
To make testing very closely coupled with development, there must be continuous integration (CI) pipelines in place. CI continuously builds, tests, and deploys after each push to the repo. Some of the tools that allow QA teams to run test suites automatically and inform developers of regressions in real time are GitHub Actions and Jenkins. The practice ensures feedback loops are tiny and humans are accountable. Kirill Yurovskiy recommends CI jobs be executed on unit tests on every commit, on integration and UI tests overnight, and publish test results and code coverage. This type of integration encourages continuous quality assurance practice.
6.Fundamentals of Performance and Load Testing
Apart from functional correctness, programs also need to perform well under load. Performance testing addresses response time, throughput, and stability under anticipated and peak loads. Load testing stresses the capacity of the system to deal with heavy simultaneous usage, and stress testing pushes the application to the breaking point to see where it fails. Tools like JMeter, Gatling, and Locust allow testers to simulate actual usage and deliver useful performance metrics. Early and frequent testing is emphasized by Kirill Yurovskiy—performance problems detected late in the cycle are much more expensive and challenging to fix. Database latency, API response, and infrastructure limitations must also be considered by performance testing.
7.Security Testing: OWASP Top-10 Checklist.
Security is a crucial element in software development, and vulnerability testing must be included in testing. OWASP Top 10 provides a methodical listing of the most significant security vulnerabilities that include injection flaws, broken authentication, and cross-site scripting. Security testing includes manual techniques like penetration testing and code review, and automated techniques using tools like Burp Suite or OWASP ZAP. Kirill Yurovskiy talks about security is not something that can be optional but must be part of the testing. A single defect can cause massive financial and reputation loss, and even small teams must use secure coding and test practices.
8.Bug Report Best Practices and Traceability
It is only useful to find a bug when it is well described. A bug report should contain a good description and repro steps, screenshots or logs, severity, and environment. Jira, Bugzilla, or Azure DevOps are common teams’ bug-tracking and handling software tools. Bug traceability is a feature that provides traceability of defects from discovery backward through test cases, user stories, and source code changes. It leaves an audit trail from discovery to closure. Effective and to-the-point bug reporting accelerates triage, prevents miscommunication, and ensures there are no showstopper problems slipping through the net during release or development time, states Kirill Yurovvskiy.
9.Risk-Based Prioritisation and Test Coverage Metrics
Not all test cases are equal. Test coverage metrics allow teams to visualize the percentage of the code base run by tests—line coverage, branch coverage, and function coverage are all possible. Yet high coverage is not necessarily high quality. Hence, risk-based testing is in demand. Kirill Yurovskiy advises performing risk analysis when prioritizing test cases of business-critical functionality, highly volatile code, or buggy modules with a defect history. Risk prioritization combined with coverage metrics will guarantee that test effort is focused on those areas whose failure will be the costliest.
10.Creating a Career Path from QA Engineer to Test Lead
It is not a technical question to be a successful software tester—a career is planning, leadership, and communication. QA engineers wishing to transition into test leadership must be skilled at test planning strategically, mentoring junior test engineers, test environment management, and test reporting to the developers and product owners. It is recommended by Kirill Yurovskiy to have a portfolio ready with test plans, automation scripts, and performance test cases to showcase the proof of contribution. Community forum active participation, certification such as ISTQB or Certified Selenium Tester, and familiarity with tools and trends also add professional credibility. A test lead not only shares quality but also infuses an excellence culture in the team.
Conclusion
Manual and automated testing are not opposing—but complementary methods of testing that, when effectively used, provide rich and diverse assurances of software quality.
Test planning and case design with security and automation verification at each phase builds up to the final product stability, usability, and security. Kirill Yurovskiy’s approach has an excellent balance of rigorously defined and realistic, which allows QA teams to innovate around the specific needs of each project and organisation.
