Software Testing FAQs

Software testing ensures that applications are free of bugs, meet user expectations, and perform reliably. It helps prevent costly errors in production and enhances user satisfaction.

Common types include:
Functional Testing: Validates that features work as expected.
Non-Functional Testing: Tests performance, usability, security, etc.
Manual Testing: Performed by humans without automation tools.
Automation Testing: Uses scripts and tools to automate repetitive tasks.
Unit Testing: Focuses on individual components or units of code.
Integration Testing: Ensures modules work together correctly.
System Testing: Tests the entire system end-to-end.
Regression Testing: Verifies that recent changes haven't introduced new defects.
User Acceptance Testing (UAT): Confirms the product meets business requirements.

QA (Quality Assurance) focuses on improving processes to prevent defects, while testing focuses on finding defects after development.

The Software Testing Life Cycle (STLC) includes phases like:
Requirement Analysis
Test Planning
Test Case Development
Test Environment Setup
Test Execution
Test Closure

A test case is a set of conditions or variables under which a tester determines whether a system satisfies requirements or works correctly.

A good test case is clear, concise, specific, reusable, and covers all possible scenarios (positive and negative).

Defect tracking involves identifying, documenting, and managing issues found during testing using tools like JIRA, Bugzilla, or TestRail.

Exploratory testing is an unscripted approach where testers explore the application dynamically to uncover unexpected issues.

Smoke testing is a quick check to ensure the most critical functionalities of an application work after a build.

Manual testing involves testers executing test cases manually without using automation tools.

Manual testing is ideal for exploratory, usability, and ad-hoc testing, as well as when automation isn't feasible or cost-effective.

Advantages include flexibility, ability to detect visual/UI issues, and no need for scripting knowledge.

Disadvantages include being time-consuming, prone to human error, and unsuitable for large-scale or repetitive tasks.

Use clear language, focus on one functionality per test case, include preconditions and steps, and define expected results.

Boundary value analysis tests input values at the edges of acceptable ranges to catch potential errors.

Equivalence partitioning divides inputs into groups that are expected to behave similarly, reducing the number of test cases.

Automation testing uses scripts and tools to execute test cases automatically, reducing manual effort and increasing efficiency.

Automation is suitable for repetitive, time-consuming, or regression tests, especially in agile and CI/CD environments.

Benefits include faster execution, increased accuracy, reusability of test scripts, and better coverage.

Limitations include high initial setup costs, inability to handle subjective aspects like usability, and maintenance overhead.

Popular tools include Selenium, Cypress, Appium, TestComplete, Katalon Studio, and Playwright.

A test automation framework is a set of guidelines, tools, and libraries used to design and execute automated tests efficiently.

Selenium is an open-source tool for automating web browsers. It's popular due to its flexibility, support for multiple programming languages, and wide adoption.

Selenium WebDriver is used for browser automation with programming languages, while Selenium IDE is a record-and-playback tool for simpler tests.

Cross-browser testing ensures that an application works consistently across different browsers (e.g., Chrome, Firefox, Safari).

CI integrates automated tests into the development pipeline to validate code changes continuously.

Performance testing evaluates how an application performs under various conditions, such as load, stress, and scalability.

Types include:
Load Testing: Tests the system under expected user loads.
Stress Testing: Evaluates behavior under extreme conditions.
Spike Testing: Checks response to sudden increases in traffic.
Endurance Testing: Assesses long-term stability.

Apache JMeter is an open-source tool for performance and load testing.

Metrics include response time, throughput, CPU/memory usage, error rate, and concurrent users supported.

API testing validates the functionality, reliability, and security of APIs (Application Programming Interfaces).

Tools include Postman, SoapUI, RestAssured, and Swagger.

REST uses lightweight JSON/XML formats over HTTP, while SOAP is protocol-based and uses XML exclusively.

Steps include sending requests, validating responses, checking status codes, and verifying data integrity.

Skills include analytical thinking, attention to detail, knowledge of testing tools, programming basics (e.g., Python, Java), and familiarity with SDLC/STLC.

While not always mandatory, coding skills are increasingly important, especially for automation testing roles.

Certifications like ISTQB, CSTE, and Selenium/automation-specific courses add value to a tester's profile.

Learn programming languages (e.g., Python, Java), practice automation frameworks (e.g., Selenium), and take online courses.

The future lies in AI-driven testing, DevOps integration, shift-left testing, and increased reliance on automation.

Shift-left testing involves starting testing earlier in the development lifecycle to identify issues sooner.

Crowdtesting leverages a community of testers to test applications across diverse environments and devices.

AI helps in test case generation, defect prediction, self-healing tests, and intelligent test prioritization.

A test plan is a document outlining the scope, objectives, resources, schedule, and approach for testing activities.

Risk-based testing prioritizes testing efforts based on the likelihood and impact of risks.

A test environment is a setup that mimics the production environment for executing tests.

Verification checks if the product is built correctly (static analysis), while validation ensures it meets user needs (dynamic testing).

A traceability matrix maps requirements to test cases to ensure complete coverage.

Smoke testing is a shallow check of critical functionalities, while sanity testing is a deeper check of specific functionalities after minor changes.

The V-model aligns testing phases with corresponding development phases, emphasizing early testing.