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Ad hoc testing is a popular testing method that's used by a lot of different QA teams, even though they may not use it all the time. It involves a tester trying to break a system by randomly executing different functions.

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There are many ways to test software. Some Types of Software Testing are conducted by software developers while some are conducted by specialized quality assurance staff. Here are the different types of software testing with brief descriptions for each. Read More – Types of Software Testing. | Testing Type | Short Definition | |---|---| | Manual Testing | Testing performed manually without automation tools to verify functionality. | | Automation Testing | Testing using scripts and tools to execute test cases automatically. | | White Box Testing | Testing internal code structure and logic with access to source code. | | Black Box Testing | Testing functionality based on requirements without knowing internal code. | | Grey Box Testing | Testing with partial knowledge of internal system structure. | | Functional Testing | Testing the system against functional requirements and specifications. | | Non-Functional Testing | Testing system performance, reliability, usability, and other quality attributes. | | Unit Testing | Testing individual components or modules independently. | | Integration Testing | Testing interaction between combined modules. | | System Testing | Testing the complete integrated system as a whole. | | Performance Testing | Testing system speed, responsiveness, and stability under workload. | | Usability Testing | Testing how user-friendly and easy the application is to use. | | Compatibility Testing | Testing application performance across different devices, browsers, and environments. | | Incremental Testing | Testing modules step by step by integrating them gradually. | | Non-Incremental Testing | Testing all modules together after complete integration. | | Top-Down Testing | Testing higher-level modules first, then lower-level modules. | | Bottom-Up Testing | Testing lower-level modules first, then higher-level modules. | | Load Testing | Testing system behavior under expected user load. | | Stress Testing | Testing system stability under extreme workload conditions. | | Testing system performance when user load increases or decreases. | | | Stability Testing | Testing system reliability over an extended period. |

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Test automation should be integrated into CI/CD, focus on high-value tests, and complement manual exploratory testing to catch regressions and accelerate feedback.

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Immediately report the bug, analyze root cause, assess impact, coordinate a fix, and improve test coverage to prevent recurrence.

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A test case is a set of conditions or actions that are executed to verify a particular feature or functionality of a software product. Test cases are written based on the requirements and specifications of the software and are used to validate that the application behaves as expected under various scenarios. A test case typically includes: - Test Case ID: A unique identifier for the test case. - Test Case Title: A brief description of the functionality being tested. - Pre-Conditions: Any conditions or setup steps that must be met before executing the test case. - Test Steps: A detailed sequence of actions or inputs that the tester needs to perform in order to execute the test. - Expected Results: The expected behavior or output that should occur after executing the test steps. - Actual Results: What actually happened when the test was executed (documented during testing). - Post-Conditions: Any conditions that must be satisfied after the test case execution. - Pass/Fail Criteria: Criteria that indicate whether the test case passed or failed based on comparing the actual results with the expected results. Test cases can be used in both manual and automated testing to ensure software works as expected in different scenarios.

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The best approach is to prioritize the most basic test cases to ensure all the most crucial aspects of the software are tested. Another judicious idea is to rely on customer feedback to understand the most important areas of the software during real world use and focus on those areas. Time management and an efficient workflow are crucial elements of QA and the interviewee should have a clear idea about these novel approaches.

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Follow the approach below when you are in a dilemma about categorizing the bug: - Discuss the business impact of the defect with the PO. - Ask the developer about the technical impact the defect might have. - Refer to past examples where similar defects have been reported to see how they were categorized. - Document and make suggestions about severity/priority, but let leads finalize.

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White Box Testing examines the internal structure, logic, and code of the software.

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Test Suite is a collection of test cases. The test cases which are intended to test an application.

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Test Closure activities fall into four major groups. Test Completion Check: To ensure all tests should be either run or deliberately skipped and all known defects should be either fixed, deferred for a future release or accepted as a permanent restriction. Test Artifacts handover: Tests and test environments should be handed over to those responsible for maintenance testing. Known defects accepted or deferred should be documented and communicated to those who will use and support the use of the system. Lessons learned: Analyzing lessons learned to determine changes needed for future releases and projects. In retrospective meetings, plans are established to ensure that good practices can be repeated and poor practices are not repeated Archiving results, logs, reports, and other documents and work products in the CMS (configuration management system).

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A test report is a document that provides an overview of testing objectives, activities, and results. It is necessary to summarize testing results and compare them against expectations. It helps us determine if the product is ready for release or not. Additionally, it allows us to see the current status of the project and assess the quality of the product

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If testers find any mismatch in the application/system in testing phase then they call it as Bug.

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A good test case should have the following characteristics:Clarity and Conciseness: The test case should be clear and easy to understand, with no ambiguity. Coverage: It should cover all the functional requirements and scenarios, including edge cases. Repeatability: The test case should yield the same results every time it is executed.Traceability: It should be traceable to the requirements it is verifying. Independent: Each test case should be independent and not reliant on the results of other test cases. Reusable: It should be reusable across different versions of the application with minimal modifications.

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First, I would test basic functionality like valid and invalid username/password combinations, empty fields, case sensitivity, and account lock after multiple failed attempts. Then I would check boundary cases like max length, special characters, and SQL injection in inputs. From a security side, I'd verify HTTPS, session timeout, CAPTCHA after multiple attempts, and token expiry. I'd also test UI/UX like error messages, tab order, password masking toggle, and mobile responsiveness. Finally, I'd prioritize critical login success/failure cases as P0, security as P1, and UI polish as P2.

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Test deliverables, also known as test artefacts, are any by-products generated while conducting tests, such as documents, tools and equipment. These are shared with stakeholders and team members across the entire SDLC.

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Quality Assurance: Quality Assurance involves in process-oriented activities. It ensures the prevention of defects in the process used to make Software Applications. So the defects don't arise when the Software Application is being developed. Quality Control: Quality Control involves in product-oriented activities. It executes the program or code to identify the defects in the Software Application.

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| Term | Definition | |---|---| | Bugs | A bug is an error in the software, which causes it to malfunction, typically caused by a coding error. Bugs are submitted by Developers and detected prior to product release. | | Defects | A defect refers to a system error that means the software cannot function as intended. There are three types of defect: Wrong – incorrect implementation of requirements Missing – a specification has not been implemented Extra – a specification has been implemented that was not required by the end-user | | Errors | Errors refer to problems with the code itself, which are commonly caused by the Developers not understanding the requirements. | Fun fact: The name ‘bug' originated from the first bug ever found, where an actual insect was stuck in malfunctioning hardware.

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The candidate should describe an instance of ad hoc testing, its effectiveness in finding unexpected issues, and explain that ad hoc testing is used for quick, informal checks while exploratory testing is more structured and monkey testing is random, with selection depending on context and goals.

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A bug can be assigned a severity rating from low to high. Here is an outline of what each severity type would look like: | Severity | Description | |---|---| | Low | Software may have user interface bugs and some accessibility issues. The defect is an issue, but can be left until more serious defects have been fixed. | | Medium | The defects should be dealt with in the regular course of the development activities, however, it is not urgent. | | High | The software at this level of severity will likely be crashing under high workloads or specific user actions and could be exposing sensitive data, thus revealing high-priority security problems that must be dealt with as soon as possible. | As an experienced Software Tester, you should be able to identify each level of severity and apply it to real-life situations, and discuss this with interviewers confidently.

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The Software Testing Life Cycle (STLC) is a series of specific steps conducted during the testing process to ensure software quality. It consists of the following phases:Requirement Analysis: Understanding and analyzing the testing requirements based on the client's needs. Test Planning: Developing the test plan and strategy, including resource planning and tool selection. Test Case Development: Creating detailed test cases and test scripts. Test Environment Setup: Preparing the hardware and software environment in which the testing will be conducted. Test Execution: Executing the test cases and logging the outcomes. Test Cycle Closure: Evaluating the cycle completion criteria and preparing test closure reports.

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It is a process where the testers test the application by having pre-planned procedures and proper documentation.

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Comprehensive test coverage can be ensured by using strategies like traceability matrices, which map requirements to test cases, and applying test design techniques such as equivalence partitioning and boundary value analysis. Regular reviews and peer testing also contribute to thorough coverage.

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Document instability, isolate failures, and communicate risk early.

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There are several potential answers to this question. Company culture will play a large part in differentiating a good from bad answer. For instance, if teamwork is important within the product team, a candidate who is driven by internal competition might not be the best fit.

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The concept of 100% test coverage can really divide software engineers, as it doesn't guarantee test quality. High coverage doesn't automatically mean well-tested software; the focus should be on test quality and critical system behaviors. Achieving 100% test coverage involves ensuring every part of the codebase is tested, but in practice, this is challenging and often impractical due to resource and time constraints. To strive towards high test coverage, one can implement several strategies: - Automated Testing: Utilize automated testing tools to create and run a comprehensive suite of tests that cover various scenarios and edge cases. - Test-Driven Development (TDD): Adopt TDD methodologies, where tests are written before the code itself. This ensures that the code developed is always accompanied by tests. - Code Reviews: Conduct thorough code reviews to identify untested parts of the codebase and ensure new code is covered by tests. - Coverage Analysis Tools: Use code coverage analysis tools to measure the current level of test coverage and identify areas that need more attention. - Incremental Improvement: Focus on improving test coverage incrementally by prioritizing critical and high-risk areas of the code first.

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All software has a target user. A user story describes the user's motivations and what they are trying to accomplish by using the software. Finally, it shows how the user uses the application. It ignores the design and implementation details. A user story aims to focus on the value provided to the end-user instead of the exact inputs they might enter and the expected output. In a user story, the tester creates user personas with real names and characteristics and tries to simulate a real-life interaction with the software. A user story often helps fish out hidden problems that are often not revealed by more formal testing processes.

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In a Risk-Based Testing Strategy, the first step would be to identify potential risks in the software that could affect its functionality or performance. These risks are then prioritized based on their impact and likelihood of occurrence. The testing effort is then directed towards the most significant risks first. This approach ensures that the most critical areas of the software are tested thoroughly, even in a scenario where there might not be enough time to test everything.

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- Appium (Automation) - XCUITest (iOS) - Sauce Labs, BrowserStack (Cloud Testing)

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One important metric is defects per test cycle, as it gives insight into the quality of the software and helps track progress over time. The choice of metric depends on the project goals, but consistency in measuring quality is critical.

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Exploratory mindset and curiosity. The answer should describe a specific, innovative approach like boundary value testing, chaos engineering, or unusual user behavior simulation.

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I'd test valid file types and size limits, including minimum and maximum boundaries. Then invalid cases like unsupported file types, corrupted files, zero-byte files, and double extensions like file.jpg.exe. I'd check security risks like executable uploads, path traversal, and embedded scripts. UI testing includes progress bar, cancel upload, drag-drop, and multiple uploads. I'd verify server-side validation because client-side validation alone is not secure.

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An interviewer might ask questions like these related to the subject: How do you incorporate continuous testing? What is your experience with implementing QA in a CI/CD pipeline?

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QA should start as early as possible in the software development lifecycle. By involving QA testers and analysts at the planning and requirements phase, potential defects can be detected earlier, reducing rework and ensuring a smoother development process.

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As the name suggests, automated testing, which is also called test automation, is the programmatic execution of the tests. The tester uses an automation tool or software like Selenium to write code that performs the following tasks. - Automatically run the software. - Feed the input data to the system. - Examine the output with the expected outcome. - Fail the test if the results don't match. Otherwise, pass the test. Once a test is automated, you can run it as often as you want, to check if any new code has broken it. It enables you to spend your time on other high-value tests, such as exploratory testing that help find bugs that an automated test would miss. Automated testing is beneficial for repetitive testing with inputs that don't change frequently. Humans get tired and bored from conducting the same tests repeatedly and seeing the same results. It's easy to make mistakes when you are testing a feature for the twentieth time. Software is much better at doing repetitive tasks without getting tired or making mistakes than a human operator would.

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Smoke testing is a quick test of the critical functionalities of a software build. It ensures that the core features work as expected and that the build is stable enough for further testing.

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| Black-box Testing | White-box Testing | | |---|---|---| | Definition | Write tests without visibility into internal code or structure. | Write tests with full visibility into internal code and structure. | | Goal | User experience, security, compatibility. | Code quality, logic correctness, optimization. | | Testing levels | UI end-to-end testing Compatibility testing | Unit testing Integration testing Static code analysis | | Tester | Business stakeholders Manual test engineers | Developers |

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Usability testing evaluates how easy it is for users to interact with the software. It measures the application's user-friendliness, including how intuitive and efficient it is for users to complete tasks.

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In my previous role, we faced a critical situation where a major product release was approaching, and we discovered several high-severity bugs during the final testing phase. The challenge was to decide whether to delay the release or proceed with known issues.I convened a meeting with key stakeholders, including the development, product management, and QA teams. We conducted a risk assessment to evaluate the impact of the identified bugs on the user experience and overall functionality. After thorough discussion and analysis, I decided to delay the release by a week. This decision allowed us to address the critical bugs and perform additional testing to ensure a high-quality product launch. I communicated the rationale behind the decision to the entire team, emphasizing the importance of delivering a reliable and user-friendly product. We also devised a detailed plan to expedite the bug-fixing process and improve our testing strategy for future releases. This decision, though difficult, ultimately led to a successful product launch with positive customer feedback.

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Bugs are typically prioritized based on severity and impact. The categories include: - Critical (must be fixed immediately) - High - Medium - Low

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Use the STAR method to describe a hypothetical situation involving a QA process, the tasks you'd be responsible for to ensure detailed attention to the project, the actions you would take, and the results you would anticipate. Take the opportunity to describe your QA methods and approaches in detail and how you would apply them to future projects.

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To ensure alignment between the testing team, development team, and product roadmap, I implement the following strategies:Regular Communication: Conduct daily stand-up meetings and weekly sync-ups to discuss progress, roadblocks, and upcoming tasks. This ensures everyone is on the same page. Collaborative Planning: Involve QA in the early stages of product planning and requirement gathering. This allows testers to understand the product vision and contribute to the development of testable requirements. Shared Goals: Establish common objectives and KPIs that align with the overall project goals. This fosters a sense of shared responsibility and teamwork. Integrated Tools: Use integrated tools for project management, test management, and defect tracking (e.g., Jira, TestRail) to ensure transparency and seamless collaboration. Cross-functional Training: Encourage cross-functional training sessions where developers and testers share knowledge and skills, promoting mutual understanding and collaboration.

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This interview question helps you to uncover how much research the candidate did before meeting with you, and it demonstrates their ability to think on the spot.

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A successful QA tester possesses strong analytical skills, attention to detail, good communication skills, problem-solving abilities, technical knowledge, and a solid understanding of various testing tools and methodologies.

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Equivalence Class Partitioning is a black-box software testing technique that divides the input data into partitions of equivalent data from which test cases can be derived. - In this approach, test cases are designed to cover each partition at least once. - It divides the input data of software into different equivalence data classes.

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ATDD is a practice where the acceptance criteria are defined in collaboration with stakeholders before the actual development begins. These criteria are then turned into automated tests to ensure the functionality meets stakeholder expectations.

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Load testing and stress testing are both performance testing techniques, but they have different objectives: - Load Testing: - Load testing evaluates how the system performs under expected normal conditions. It measures the system's ability to handle a specified number of concurrent users, transactions, or data volume. - Objective: To determine the system's behavior under expected load and verify that it performs within acceptable limits (e.g., response time, throughput). - Example: Simulating 100 users simultaneously logging in to a web application to ensure it can handle the traffic. - Stress Testing: - Stress testing pushes the system beyond normal or expected usage conditions to evaluate how it behaves under extreme load. This type of testing helps identify the system's breaking point and its ability to recover from failures. - Objective: To determine the system's robustness and stability under extreme conditions and evaluate how it behaves when resources (e.g., memory, CPU) are overloaded. - Example: Simulating 1,000 users on the same web application to observe how the system behaves when it exceeds its designed capacity. In summary, load testing checks how the system performs under normal usage, while stress testing evaluates its behavior under extreme conditions or overload.

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A test scenario is a high-level idea of what to test, like “Verify user login functionality.” A test case is detailed step-by-step instructions with test data and expected results, like entering valid email and password and verifying dashboard loads. A test suite is a collection of related test cases grouped together, like all login-related test cases. Test scenarios come from requirements, test cases come from scenarios, and test suites are organized for execution cycles. All of this is tracked in RTM to ensure requirement coverage.

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I have experience working with a variety of automated testing tools and frameworks, including Selenium, JUnit, TestNG, and Appium for mobile testing. Automated testing allows for efficient and repeatable testing of software applications. I've developed and maintained test scripts, set up test environments, and integrated automated tests into continuous integration pipelines. Automation not only speeds up testing but also provides early feedback on code changes, improving overall software quality.

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When the results are loaded slowly, it may mean the network is slow, the API response is sluggish, or the overall application performance is sluggish. As a tester, you could diagnose the outcome by checking the following: - Network logs are used to check API response times as well as overall network performance. - Compare pagination vs full-list load and validate how they differ. - Try various filters to refine the output and compare the results. - Test with large datasets to ensure the results do not get slower. - Analyze browser profiling for rendering bottlenecks. - Report performance metrics.

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Software testing is part of QC and validates the product against requirements.

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Low: Software may have user interface bugs and some accessibility issues. The defect is an issue, but can be left until more serious defects have been fixed. Medium: The defects should be dealt with in the regular course of the development activities, however, it is not urgent. High: The software at this level of severity will likely be crashing under high workloads or specific user actions and could be exposing sensitive data, thus revealing high-priority security problems that must be dealt with as soon as possible.

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Scope, approach, risks, timelines, environments, and responsibilities.

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The Software Testing Life Cycle, or STLD, are the steps or activities used to test software applications to ensure a high-quality product at the end. As an experienced Software Testing professional, you should be able to explain each stage in detail if required.

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Functional testing is testing the software to ensure that it works as per the specified requirements, while non-functional testing is testing the software for its performance, scalability, security, and other non-functional requirements.

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I'd absolutely report it. Quality is everyone's responsibility, not just what's assigned to me. I'd document it the same way I would any other bug—clearly and with reproduction steps—and log it in the system. I'd let the team know that it's outside my formal test scope, but it's worth fixing. I've never had anyone upset about finding extra bugs; the team appreciates the thoroughness. That said, I wouldn't go crazy testing every tangential area—I'd stay focused on my primary scope. But if something is clearly broken, it's worth a quick report.

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Cross Browser Testing is a type of non-functional test which helps us ensure that our website or web application works well in various browsers. Web applications rely on browsers like Google Chrome, Mozilla Firefox, Internet Explorer and Safari to function. Even though they all support web standards to some extent, there are still slight differences between them. This can pose a problem for developers who have to test their software on multiple browsers and take note of any inconsistencies. Different browsers display websites differently due to styling, and it's not possible to have every browser installed on one machine. Each browser is designed by a different company. Every browser has its own individualized features to make it stand out from the rest. When testing a website, we have to confirm that our site looks the same on all browsers.

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In software development, a user story is a description of a functionality that will be delivered to the end user. It is typically written from the user's perspective and captures what the user needs or wants. A good user story should be small and self-contained, so that it can be easily implemented by the development team. User stories are a key part of agile software development, and help to ensure that the final product will meet the needs of the end users. They also help to break down complex functionality into smaller, more manageable pieces.

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Verification: Verification is a process that ensures the software meets quality standards and the specification. Verification is an objective process and a type of static testing, since you test the software without actually using it, through code walkthroughs and reviews. Validation: Validation is a process that checks whether the software functionality meets customer requirements and is done at the end of the development process after verifications are complete. Validation is a more subjective process in comparison to verification, and is a type of dynamic testing as it is tested whilst running in a test environment.

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In software testing, there are four testing levels. - Unit Testing or component level testing - Integration Testing - System Testing - Acceptance Testing

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SPICE stands for Software Process Improvement and Capability Determination. In the field of software development processes, SPICE is a standard framework for assessing the efficiency and effectiveness of the development process. IEC (International Electrotechnical Commission) and ISO (International Organization for Standardization) jointly developed SPICE.

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When faced with limited time for testing, prioritization is key. To prioritize testing, you need to consider the risk associated with each functionality and the impact that a defect in that functionality would have on the software. High-risk functionalities should be tested first, followed by medium-risk functionalities, and finally, low-risk functionalities.

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A test plan is a document that is monitored by the Testing Manager and provides an outline of the entire test process, including what was tested, when, how and why. A test plan must include the test strategy, objectives, schedule, estimations, deadlines and the resources required.

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Example Answer: I'd look beyond traditional metrics and add a few AI-specific ones. Agent Assist Rate tells you what percentage of test cases, triage events, or summaries involved AI assistance. Human Override Rate tells you how often the team corrected or rejected AI suggestions, which is a trust and accuracy signal. Scenario Coverage Delta measures the gap between what's actually happening in production and what your test suite covers, as identified by AI observation tools. And Review Time Saved quantifies how much faster humans can review and finalize AI-generated content compared to writing from scratch. Combining these with DORA metrics like Change Failure Rate gives you a complete picture of whether AI is actually improving quality outcomes or just generating activity.

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Verification is checking if we're building the product right (does it match the specs?). It's done without running the code, like through reviews or static analysis. Validation is confirming we're building the right product (does it meet user needs?). This involves actually executing the software, like functional tests or user trials. Verification catches early mistakes; validation ensures the end result is useful.

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Automation is important for regression, repetitive tests, and CI/CD. Tests that cannot be automated include exploratory, usability, and ad-hoc tests.

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The dictionary definition of regression is the act of going back to a previous place or state. In software, regression implies that a feature that used to work suddenly stopped working after a developer added a new code or functionality to the software. Regression problems are pervasive in the software industry, as new features are getting added all the time. Developers don't build these features in isolation, separate from the existing code. Instead, the new code interacts with the legacy code and modifies it in various ways, introducing side effects, whether intended or not. As a result, there is always a chance that introducing new changes may negatively impact a working feature. It's important to keep in mind that even a small change has the potential to cause regression. Regression testing helps ensure that the new code or modifications to the existing code don't break the present behaviour. It allows the tester to verify that the new code plays well with the legacy code.

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Be practical while answering these kind of real time manual testing interview questions. You can say like it totally depends on the test case complexity and size. Some test cases have few test steps and some have more test steps. A sample answer is “In my previous project, we generally execute 30-40 simple test cases (like login functionality) per day, 10-20 medium test cases (like Assigning user roles) per day, and 5-10 complex test cases (complete purchase flow) per day.

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A good bug report should be clear and detailed so developers can fix it quickly. I'd include a short title like “App crashes on login with invalid password,” then list the environment (e.g., iPhone 14, iOS 17), steps to reproduce (1. Open app, 2. Enter wrong password, 3. Hit login), what happened vs. what should happen, screenshots or logs, how often it occurs, and its severity (like critical if it blocks users). This way, it's easy to track and resolve without back-and-forth.

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Versioning and maintenance of automated test scripts are critical to ensure that tests remain effective and scalable over time. Here's how to handle these aspects: - Version Control with Git: - Store your test scripts in a Git repository (e.g., GitHub, GitLab, Bitbucket) to track changes and maintain version control. Each test script should be treated like source code, so version control ensures that changes are logged and revertible. - Use branching strategies (e.g., feature branches, release branches) to ensure that changes to test scripts are isolated and reviewed properly. - Create a Versioning Strategy: - Assign versions to your test scripts, particularly when major changes are made to the framework or when significant features are added or modified. - Tag releases in Git to mark specific points in time, like when the test scripts are aligned with a particular application version. - Follow semantic versioning (e.g., v1.0.0 for the first release, v1.1.0 for minor updates, v2.0.0 for major changes) to clearly define updates. - Automated Test Maintenance: - Automate the updating of tests by setting up regular reviews (e.g., quarterly) to ensure they are aligned with the application's latest version. - Implement test refactoring practices, where tests are continuously improved and optimized based on new requirements and learnings. - Maintain a test case inventory to track which tests are outdated, redundant, or no longer needed. - Use Versioned Test Data: - Ensure that test data is also versioned and aligned with the application. This can be done by using separate datasets for each version of the application. - Automate the creation and management of test data whenever possible. - Continuous Integration (CI) with Versioning: - Ensure that your versioned test scripts are integrated with your CI/CD pipeline, so each change in the codebase triggers the corresponding tests. This ensures that your scripts are executed against the most recent version of the application. - Set up branch-specific tests to ensure that tests are aligned with the respective feature or release branch. - Test Script Health Check: - Monitor and evaluate the effectiveness of automated test scripts regularly. Flaky tests should be addressed immediately, and test scripts that are no longer relevant should be removed or archived.

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Answers vary, but often include exploratory testing, test automation design, or debugging complex issues.

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There are various ways to test software. Software developers conduct some types of testing while other kinds of software testing are done by QAs. The following are several types of software testing

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I'd start by reading the feature's requirements to understand what it's supposed to do. Then, I'd make a simple test plan outlining normal use cases (like what happens when it works perfectly) and edge cases (like what if the internet cuts out?). For a payment feature, I'd test different payment methods, amounts, and errors on various phones and OS versions. I'd do manual tests first to mimic real users, then maybe automate repetitive parts if tools like Appium are available. Finally, I'd document any bugs with steps to recreate them and retest after fixes.

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Maintain Clear Communication: - Collaborate closely with business analysts and stakeholders to understand changes. - Update Test Artifacts: - Revise test cases and scripts to reflect updated requirements. - Maintain a traceability matrix to ensure all requirements are tested. - Prioritize Testing: - Focus on critical changes first. - Allocate time for regression testing to ensure no existing functionality is broken. - Leverage Agile Practices: - Conduct regular sprint reviews and retrospectives to adapt to evolving requirements efficiently.

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Test plans are documents that outline the strategy and approach of a software testing effort. Test strategies are rules that establish the test design. A long-term test plan can change, whereas a tester cannot adjust a test strategy.

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Test planning involves outlining the objectives, scope, approach, resources, and schedule for testing activities. My approach includes the following steps:Defining the Objectives: Clear goals and objectives of the testing process. Scope Identification: Determining what will be included and excluded in the testing. Resource Planning: Identifying the required resources, including tools, environments, and personnel. Schedule and Milestones: Setting timelines and key milestones for testing activities. Risk Analysis: Identifying potential risks and mitigation strategies. Test Plan vs. Test Strategy:Test Plan: A detailed document outlining the specifics of the testing activities, including test objectives, scope, resources, schedule, and deliverables. It is project-specific. Test Strategy: A high-level document that outlines the general approach and principles for testing within the organization. It is typically static and applies across multiple projects.

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The following steps can assist in resolving issues during testing: - Record: Keep track of any problems that arise and resolve them. - Report: Inform higher-level managers of the issues. - Control: Establish a process for managing issues.

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Quality audits are part of software testing where testers compare products to the expected standards and follow specific steps, including: conducting a process evaluation, completing a compliance assessment, carrying out a documentation review, analyzing the software's performance, and reviewing defect management processes. Quality audits ensure software complies with industry best practices.

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I call out risks early and help prioritize what truly matters.

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Once you ship the software to the customers after alpha testing, the software's actual users perform the beta testing in a real production environment. It is one of the final components of user acceptance testing. Beta testing is helpful to get feedback from real people using your software in real environments.

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This is a term used by many QA departments, so you can expect a question like this during your interview. Your answer should cover that testware refers to artifacts people use to build and run tests, such as test cases, test plans, and test data.

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Example Answer: I look at triage as the "Quality Filter" for the project. It's where QA, Development, and Product Owners come together to look at the current bug backlog. My role is to present the identified defects—including their severity and impact—so the team can decide which ones are "must-fixes" for the current release and which can be safely deferred. It's about ensuring the dev team is working on the most important issues first.

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Automation Testing refers to the automation of human/manual testing processes and enables Testers to complete a wider test coverage in a short time sprint. Since this is now becoming increasingly popular in Agile and DevOps software environments, you will likely be questioned on this during your Software Testing interview.

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I have been working in manual testing for [insert number of years]. During this time, I have worked on various projects, ranging from simple to complex systems. I have hands-on experience in creating and executing test cases, documenting defects and working with developers to resolve them.

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Cause-effect graphs are related to black-box testing methods. They identify the lowest number of test cases required to test the product's full scope and use a set of decision rules that the tester specifies. These graphs help companies optimize test cases, understand system behavior, ensure they test all of the system's requirements, improve software quality, and make it easy to trace requirements to specific input-output pairings.

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An effective test strategy provides a roadmap for the entire testing process and ensures that all aspects of quality are addressed. Key elements include clearly defined objectives, a scope that outlines the specific areas to be tested, a timeline that sets milestones, and the tools and resources required for execution. It also incorporates risk analysis to anticipate challenges and provides test deliverables, such as detailed reports and defect logs.

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Yes. I have been to that kind of scenarios several times. There were companies where they had no documents at all. In that case, I had to discuss the application scenario and functionalities with the Business Analysts or developer. On the basis of that discussion, I prepared a document in consultation with Business Analysts and Developers and then started writing Plans and Test Cases.

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The candidate should discuss strategies like automating repetitive tests, taking breaks, setting goals, using checklists, and maintaining a systematic approach to ensure accuracy and consistency.

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Debugging is the act of finding and solving errors in a computer program that stops it from running properly. There are several categories of debugging, which include: - Brute force debugging - Backtracking - Cause elimination - Fault tree analysis - Program slicing

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Repeated testing of an already tested program, after modification, to discover any defects introduced or uncovered as a result of the changes in the software being tested or in another related or unrelated software components. Usually, we do regression testing in the following cases: - New functionalities are added to the application - Change Requirement (In organizations, we call it as CR) - Defect Fixing - Performance Issue Fix - Environment change (E.g., Updating the DB from MySQL to Oracle)

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Ask questions, review similar features, and test from a user's perspective.

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Combining all the modules once and verifying the functionality after completion of individual module testing. Top-down and bottom-up are carried out by using dummy modules known as Stubs and Drivers. These Stubs and Drivers are used to stand in for missing components to simulate data communication between modules.

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Debugging a failed test case involves identifying the root cause of why the test failed and resolving the issue. The process typically follows these steps: - Check Test Logs: Examine the test logs to look for any errors, exceptions, or unexpected behavior during the test execution. This can help pinpoint where the test failed (e.g., specific method calls, assertions, or UI actions). - Reproduce the Failure Locally: If the test fails intermittently, try to reproduce the failure locally by running the test multiple times. This helps in understanding whether the failure is due to environmental factors or a legitimate defect in the code. - Isolate the Problem: Narrow down the cause of the failure by checking if the issue is related to: - Test setup or configuration (incorrect test data, missing environment variables). - Code changes (new code changes might have introduced issues). - Test environment (differences between the test environment and the production environment). - Dependencies (issues with third-party services, APIs, or libraries). - Check Dependencies: If the failure is due to external dependencies (e.g., databases, APIs), mock or stub those dependencies to isolate the test and verify if the failure is within the test code or the application. - Review Test Case Logic: Ensure that the test case itself is valid. Check for logical errors, incorrect assertions, or outdated test steps. - Debugging Tools: Use debugging tools like breakpoints, interactive debuggers, or logging statements to step through the test and inspect the state of variables, method calls, and returned values at each stage. - Collaborate: If the issue is difficult to resolve, collaborate with developers or other team members to troubleshoot the failure. They may have more insight into the application's behavior or the area being tested. - Fix and Re-Test: Once the root cause is identified, fix the problem and re-run the test to ensure it passes. If necessary, improve the test case to handle similar issues in the future.

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- Keep them simple and clear - Cover positive and negative scenarios - Use reusable test steps 4 .Ensure traceability to requirements

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- DevAssure (end-to-end test automation tool) - Appium (Mobile Applications) - JMeter (Performance Testing) - Postman (API Testing) - TestNG, JUnit (Test Frameworks) - Cypress (Web UI Testing) - Playwright (Modern Web Automation)

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End-to-end thought process, from reading requirements to exploratory and regression coverage. Understand the feature, design test scenarios, prioritize based on risk, and execute exploratory tests.

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- Test Strategy: High-level document describing the testing approach. - Test Plan: Detailed document with specific test cases and execution steps.

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Check length rules, complexity, masking, and copy-paste behavior.

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Quality is a shared responsibility across the entire team, including developers, testers, product managers, and operations.

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Performance tests are run to assess speed, scalability, stability, and resource usage under various loads, such as peak traffic or long-term usage.

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Example Answer: I think QA is moving from a "testing function" to a "quality intelligence function." The mechanical parts of testing (writing scripts, running regressions, triaging failures) are being absorbed by AI. What remains, and grows in value, is the strategic layer: understanding what quality means for the business, setting the objectives that guide AI agents, designing the governance frameworks that keep AI accountable, and doing the exploratory, creative, adversarial testing that AI can't do well. The QA engineers who thrive will be the ones who learn to work alongside AI, not compete with it. They'll be orchestrators, not executors.

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I've faced challenges like flakiness in tests, unstable environments, and high maintenance of test scripts. I resolved them by optimizing synchronization strategies (e.g., waits), improving environment stability, and implementing modular, reusable scripts to reduce maintenance overhead.

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Managing scope change requests during a planned sprint can be challenging but crucial to maintaining productivity and project timelines. Effective management starts with a clear change control process and strong communication. Here are some steps to manage scope change requests during a sprint: - Assess the Impact: Review the new requirements to understand their impact on the current sprint and overall project. Consider the time, resources, and potential disruption to the team's workflow. - Prioritize and Evaluate: Determine the urgency and importance of the change. Align with stakeholders to evaluate whether the change adds significant value or if it can be deferred to future sprints. - Communicate Transparently: Inform the team about the change request as soon as possible. Transparency helps in setting realistic expectations and prepares the team for potential adjustments. - Adjust the Sprint Goal: Re-evaluate the sprint goals and backlog items. If the change is deemed critical and must be accommodated, reprioritize the existing tasks and adjust the sprint plan accordingly. - Document the Change: Keep detailed records of what changes were made, why they were necessary, and how the decisions were reached. This documentation can provide valuable insights for post-sprint reviews and future planning. - Seek Team Input: Gather feedback from your team regarding the feasibility and timeline adjustments. Their input is crucial for making informed decisions. - Monitor Progress: Track the implementation of the change closely. Ensure that the team stays on course and that the change is integrated smoothly without compromising quality. Managing scope change requests effectively requires flexibility, strong processes, and continuous collaboration. By balancing structure with adaptability, teams can navigate changes without derailing the sprint's progress and ensure successful project outcomes.

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End-to-end testing refers to the practice of testing a software system from the start to the finished project, ready for the end-user. This means the Tester would download the software, open and use it just like a user would – giving them the chance to test it with all dependencies and integrations, and putting it under the ultimate test in a real-life environment.

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Edge cases are those rare or extreme scenarios that push the system to its limits, like maximum users, empty inputs, or unusual combinations. For instance, in a file upload feature, an edge case might be uploading a 0-byte file or one exactly at the size limit. Testing these helps ensure the app doesn't crash under weird conditions; it's all about robustness.

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Some specific test cases used in regression testing include: Login functionality (to determine whether it works correctly after making changes), Data integrity (to validate that database structure changes don't cause data integrity problems), Performance testing (to ensure the application's response time meets expectations), and Compatibility testing (to guarantee the application is compatible with various operating systems, browsers, and devices).

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We had an important customer waiting for a new payment integration, and slipping the date would've cost us the deal. We had two days to test instead of the planned week. Rather than panic, I worked with the team to identify what had to work: the payment flow itself, basic error handling, and security considerations. We agreed to defer testing of edge cases and batch payment scenarios to a follow-up release. I communicated this scope clearly to the customer. We shipped on time, and the integration worked. We did find some minor issues in the follow-up release that we'd normally have caught earlier, but nothing critical. The key was being transparent about the tradeoff instead of just hoping we wouldn't find problems.

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Mocks and stubs are both types of test doubles used in unit testing to isolate the unit under test (UUT) from its dependencies. They allow testers to simulate behavior of real objects in the system. - Stubs: - A stub is a simple implementation of a function or method that simulates the behavior of a dependency or collaborator in the system. It returns predefined values or responses when called, without executing any actual logic. Stubs are used to simulate the behavior of external components that are not yet available or are too complex to test directly. - Use Case: Stubs are used when you need to test a specific functionality without the actual implementation of a dependency (e.g., an external service or database). def fetch_data_from_database(): return "mocked data" # A stub returning predefined data Mocks: - A mock is a more advanced type of test double that not only simulates behavior like a stub but also tracks interactions (such as method calls, arguments, and frequency). Mocks can assert whether certain methods were called and validate interactions between objects. Mocks are typically used to verify that the unit under test interacts correctly with other components. - Use Case: Mocks are used when you want to verify that specific functions or methods are being called with the correct arguments during the test from unittest.mock import MagicMock mock_service = MagicMock() mock_service.some_method.return_value = "mocked response" Differences between Mocks and Stubs: - Stubs return fixed data to allow the test to proceed. - Mocks verify interactions and ensure that the system behaves correctly in terms of method calls and arguments.

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If I discovered a critical bug just before release, I'd immediately communicate the issue to the project team and stakeholders, providing details about its severity and potential impact. I'd then propose potential solutions, such as delaying the release, issuing a hotfix post-launch, or finding a workaround depending on the situation.

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Verification takes place during the development phase to ascertain if all the specified requirements of the phase are being met. Validation takes place when the development is complete and is used to understand if the entire product meets the requirements. It is crucial for the interviewee to understand this very important distinction. Look for in-depth technical knowledge about both processes.

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Not all tests are suitable for automation, and it's important to determine which ones to automate based on factors such as: - Repetitiveness: Tests that need to be executed frequently (e.g., regression tests, smoke tests) are ideal candidates for automation, as they save time and effort in the long run. - Stability: Automating tests for stable features is more effective because frequent changes in the application can lead to high maintenance costs for automated tests. - Complexity: Complex test scenarios that involve multiple components or configurations can benefit from automation, as they are difficult and time-consuming to test manually. - Critical Business Functions: Tests that validate critical user paths or key functionality (e.g., payment processing, login flows) should be automated to ensure they are thoroughly and consistently tested. - Time Sensitivity: Time-sensitive tests that need to be executed within tight deadlines (e.g., performance tests, load tests) are good candidates for automation. - Test Environment Compatibility: Tests that require a specific environment or system configuration, or need to be executed across multiple platforms, are often better suited for automation. Tests that are infrequent, have unpredictable behavior, or require subjective evaluation (e.g., visual testing) are usually better suited for manual testing.

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Perform abnormal action on the application deliberately in order to verify the stability of the application.

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Severity and priority are both used to describe the impact and urgency of a defect, but they have different meanings and purposes: - Severity refers to the degree of impact that a defect has on the system. It describes how critical the defect is in terms of functionality or system stability. Severity is usually assigned based on the defect's technical impact, regardless of how quickly it needs to be fixed. - Examples of severity: - Critical: The system crashes or becomes completely unusable. - High: Major functionality is broken but the system can still be used with limitations. - Medium: Minor issues or functionality is impacted but there is a workaround. - Low: Cosmetic issues or minor usability problems. - Priority refers to how soon a defect should be fixed, indicating the urgency with which the defect needs to be addressed. Priority is often based on business needs, customer impact, and project deadlines. - Examples of priority: - High priority: The defect needs to be fixed immediately because it affects core functionality or user experience. - Medium priority: The defect should be fixed but can be deferred to later in the development cycle. - Low priority: The defect can be fixed at a later stage, possibly in future releases. In short, severity deals with the impact of the defect, while priority addresses the urgency of fixing it. A defect can be of high severity but low priority (e.g., a rare crash in a non-critical part of the application) or vice versa.

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Test Closure is a document that provides a summary of all the tests that are covered in the software development lifecycle. - It includes various activities like test completion reports, test completion matrix, a summary of test results, etc. - The test closure process helps the other team members to get to know about the end of the testing process. - It provides a complete report of all the errors discovered and resolved so that the source of the error can be located and resolution can be provided. Read More - Test Closure.

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State transition testing checks how a system moves from one state to another based on events. It focuses on valid and invalid transitions between states. For example, in ATM PIN entry, after 3 wrong attempts, the card gets blocked. Test cases cover correct flow, incorrect flow, and impossible transitions. It is useful for login systems, order workflows, and subscription states.

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- Identify automation opportunities and prioritize based on impact - Evaluate and select automation tools based on technical needs - Define KPIs and success criteria, and establish monitoring/reporting - Train the team and set up governance, policies, and procedures - Track effectiveness and refine the strategy as needed

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Running a system at high load for a prolonged period of time to identify the performance problems is called Soak Testing.

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Data-driven testing is a design pattern that reuses the same test flow across multiple sets of input data. | Scenario | Test Case | Data Input | |---|---|---| Login Scenario | Test Case 1 | Valid username and password combinations | | Test Case 2 | Invalid username and password combinations | The purpose of data-driven testing is to avoid hard-coding single input values. Instead, tests are parameterized and read data dynamically from sources such as databases, spreadsheets, or XML files. Data-driven testing is particularly useful for: - Input validation - Boundary testing - Error handling and exception testing - Compatibility testing across different browsers, devices, and OS configurations - Performance testing with varying data loads

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In the context of QA testing, these two terms typically refer to numbers used to name software. A build number is provided by the development team for the testing team to label software that can be installed. A release number is provided to the customer by either the dev team or the tester.

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'Gorilla testing' involves using methods to test specific software functionalities. The process requires testers to: Identify specific areas (which functionalities to test), Define testing scenarios (specific real-world scenarios), Execute tests (follow test steps), Analyze the results (observe functions and check for unexpected behavior), Iterate tests (incorporate feedback), and Report bugs (report detailed information to the development team). This approach improves software quality and ensures business requirements align with the software's critical functionalities.

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- Response Time (Time taken to load a request) - Throughput (Requests processed per second) - Latency (Delay before a response starts) - Error Rate (Failed transactions vs. total transactions)

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In addition to the broad categories described by the Testing Pyramid, I would like to hear a candidate talk about the differences between functional, UI, security, smoke, and other types of tests. There is less of an officially defined list of these types, so this is a good way to learn what categories the candidate has experience with and how they think about organizing tests.

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A/B testing is the process of comparing two versions of a webpage or other marketing asset to see which one performs better. The comparison doesn't stop with web pages – it can be app interfaces, landing pages, email marketing, etc.

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I create a detailed testing plan that outlines the scope, objectives, and timeline for each task. I also regularly communicate with my team and stakeholders to understand their priorities and adjust my testing plan accordingly. I use project management tools such as Trello, Jira, or Asana to track my progress, ensure deadlines are met, and maintain visibility into my testing tasks. Additionally, I prioritize high-risk and high-priority tasks and make sure to allocate adequate time and resources to ensure their successful completion.

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The test environment is the hardware and software set up for the testing teams to run test cases. This test environment setup varies from product to product and its configuration completely depends on the application under test requirement. The easiest way to organize a test environment is through automation. - The test environment is used by the testing teams to test the software, identify the bugs, and find a possible fix for the bugs. - A test environment is used to check the quality of the software and the impact of the application before release. Read More - Test Environment.

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Automation checks known paths. Manual testing explores behavior.

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Though it varies depending on the size and structure of the software development teams, typically, a bug can be assigned the following types of severities, going from low to high: Low - User Interface bugs. - Accessibility issues. Medium - Leaky abstractions. - Software hangs. - Users unable to perform a specific action. - Boundary conditions. High - Crashing under high load. - Business logic and/or calculation errors. - Any user action that causes the software to crash. - Exposing sensitive user data. - Security problems. - Loss of data.

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A bugfix is a build aimed at resolving a bug which is detected by the testers in the testing cycle.

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Smoke checks build stability. Sanity checks specific fixes or changes.

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In scenarios where UI changes frequently, automation is challenging. However, we can achieve automation if we focus on specific criteria as follows: - Try to use stable locators (IDs > XPaths) that will not change easily. - Implement a page object model or screen play pattern. - Prioritize API-level automation to minimize the direct impact of UI changes. - Maintain abstraction for UI locators. - Avoid automating volatile UI areas; instead, test these areas manually.

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Endurance testing is a non-functional testing type. It is also known as Soak Testing.

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Answering this question correctly demonstrates your knowledge of high-level testing concepts. When you answer, make sure you mention that test strategy involves forming an introduction, compiling a set of resources, deciding the scope, and setting a schedule for your testing and the tools involved.

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This question is your chance to highlight why you're a perfect fit for the role. Focus on your unique skills, experience, and passion for QA.

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Test Plan is a document that consists of all future testing-related activities. It is prepared at the project level and in general, it defines work products to be tested, how they will be tested, and test type distribution among the testers. Before starting testing there will be a test manager who will be preparing a test plan. Test Plan includes test objectives, scope, test types, tools, and timelines. Read More - Test Plan.

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Regression Testing: Testing team re-execute the tests against the modified application to make sure whether the modified code breaks anything which was working earlier. Confirmation Testing: Usually testers report a bug when a test fails. Dev Team releases a new version of the software after the defect is fixed. Now the testing team will retest to make sure the reported bug is actually fixed or not.

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Perform testing on the application continuously for long period of time in order to verify the stability of the application

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Being honest is key here. Discuss a specific situation where you missed a bug, how it happened, and, most importantly, what steps you took to improve your testing process afterward. This shows your ability to learn from mistakes and adapt.

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Not every test case should be automated. It should be applied where it delivers clear value, and the real value lies in automating repetitive, high-volume, and business-critical scenarios. The right approach is to evaluate stability and maintenance cost before deciding which test case to automate.

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Performance testing evaluates how an application performs under specific conditions, such as varying user loads, network speeds, or data volumes. It aims to identify performance bottlenecks, ensure the system meets performance criteria, and verify that the application can handle anticipated traffic without compromising user experience.Types of performance testing include load testing, stress testing, and endurance testing. Performance testing helps ensure the application's responsiveness, stability, and scalability.

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Sanity testing is a subset of regression testing that ensures an application functions as expected after code changes. Sanity testing acts as a checkpoint to decide whether testing can continue. This is an undocumented process that focuses purely on the functionality of the app.

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Example Answer: While I can't name the specific project, I often share a scenario where I found an "intermittent" bug—those are always the toughest. I found an issue where a session would time out only when a user switched between three different tabs during a specific API call. I used the following framework to resolve it: - Step 1: I documented the exact sequence and used observability logs to find the hidden error code. - Step 2: I explained that it was challenging because it required a very specific set of user behaviors and network conditions. - Step 3: I collaborated with the backend dev to track the session token across the microservices. - Step 4: We hit a roadblock where we couldn't replicate it in our local environment, so we had to use synthetic data in a staging environment. - Step 5: I verified the fix by running an automated "soak test" for several hours. - Step 6: The lesson learned was to always monitor session handoffs more closely in our integration tests.

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Functional testing focuses on verifying that the software performs as expected according to requirements. Non-functional testing assesses aspects such as performance, security, and usability.

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A test environment consists of a server/computer on which a tester runs their tests. It is different from a development machine and tries to represent the actual hardware on which the software will run; once it's in production. Whenever a new build of the software is released, the tester updates the test environment with the latest build and runs the regression tests suite. Once it passes, the tester moves on to testing new functionality.

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Example Answer: The role is shifting from executor to orchestrator. AI handles the repetitive, pattern-matching work that used to consume most of a tester's day: writing regression scripts, maintaining brittle locators, triaging flaky tests, generating data. That frees QA engineers to focus on the work that actually requires human judgment: exploratory testing, risk analysis, defining what "quality" means for the business, and reviewing whether AI-generated tests are actually covering the right things. The skill set is changing too. Understanding how to prompt and evaluate AI output, how to set guardrails, and how to measure whether AI is genuinely helping or just creating noise are all becoming essential.

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Problem-solving skills are an integral part of QA testing. Expert QA testers can narrow their search for errors and bugs with problem-solving skills and locate bugs faster. Problem-solving ability is also essential for helping testers select the correct tools to fix errors, consider the cost versus value risk when completing testing actions, and acknowledge which methods might create extra problems for the software in the future.

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It is important to hire a well rounded Test Engineer who is familiar with several different types of testing or find one who is willing to learn.

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In short, SDLC (Software Development Life Cycle) enables the development of high-quality, low-cost software with the shortest possible development time. A major objective of the SDLC is to produce high-quality software that meets and exceeds the expectations of customers. SDLC provides a detailed plan with a series of stages, or phases, that encompass their own processes and deliverables. By adhering to the SDLC, developers can enhance the speed of their projects and minimize risks and costs.

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A good QA leader should have: - Strong communication skills - The ability to mentor and guide the team - A focus on collaboration and problem-solving - The ability to maintain quality standards while encouraging innovation

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Yes. A low-severity issue can be a high priority if it affects a release.

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If a tester includes defects when they release software and know there are some issues with it, this is called a 'bug release.' Although bugs aren't ideal for the user experience, testers complete bug releases after serious thought and consideration, normally weighing the benefits and risks and considering project constraints before proceeding.

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The bug life cycle (also known as the defect life cycle) refers to the stages that a bug goes through from discovery to resolution. It tracks the progress of a defect as it moves through various phases until it is either fixed or rejected. The typical bug life cycle includes the following stages: - New: When a defect is first discovered and reported, it is in the "new" state. This means that it has not yet been analyzed or reviewed. - Assigned: The bug is assigned to a developer or team member who will investigate the issue. They may reproduce the defect and begin working on a solution. - Open: Once a developer acknowledges the bug, the status changes to "open." This means the bug is actively being worked on. - Fixed: Once the developer has resolved the issue (such as fixing the code), the defect moves to the "fixed" state. The bug is now ready for testing again. - Retested: After the fix is applied, testers retest the defect to ensure it has been resolved and that no new issues have been introduced. - Closed: If the bug passes testing and no further action is required, it is closed. The defect is considered fixed and no longer needs attention. - Reopened: If the defect persists after retesting, it may be reopened. This typically occurs if the fix is found to be incomplete or ineffective. - Deferred: Sometimes, a bug may be deferred if it is not critical or cannot be fixed immediately. This is common in cases where the issue does not impact the functionality or user experience significantly. - Rejected: If the bug is determined not to be a valid defect or if it is not reproducible, it may be rejected. This can happen if the issue is caused by user error or misunderstood requirements. Each stage in the bug life cycle allows for tracking, managing, and ensuring that defects are addressed in an orderly manner, with clear ownership and accountability.

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A great quality product is reliable, user-friendly, performant, secure, and meets stakeholder expectations with minimal defects.

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The candidate should be familiar with various testing types and methods, such as functional testing, regression testing, integration testing, system testing, user acceptance testing, and both manual and automated testing approaches.

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Setting up an automation framework from scratch involves several key steps that ensure scalability, maintainability, and efficiency. Here's the approach: - Requirement Gathering: - Before you begin designing the framework, gather requirements from all stakeholders (QA, development, and product teams). Understand the application's architecture, the types of tests needed (UI, API, performance), and integration points with CI/CD pipelines. - Define the goals of the automation framework (e.g., reducing regression testing time, improving test reliability). - Selecting Automation Tools: - Choose the right tools based on the application's technology stack. For web applications, tools like Selenium, Cypress, or Playwright are popular. For APIs, RestAssured, Postman, or SoapUI are commonly used. If mobile testing is needed, Appium or UIAutomator could be appropriate. - Also, select tools for continuous integration (e.g., Jenkins, GitLab CI, CircleCI) and version control systems (e.g., Git). - Design the Framework Architecture: - The architecture should be modular and reusable. A common design pattern is the Page Object Model (POM) for UI tests, which abstracts the UI elements into classes, making maintenance easier when the UI changes. - Consider whether the framework will be built on a Keyword-Driven, Data-Driven, or Hybrid approach based on the needs of your tests. - Choose between a Linear framework (simpler, for smaller projects) or a Modular framework (more complex, for larger applications). - Integrating Reporting and Logging: - Use reporting tools such as Allure, ExtentReports, or ReportPortal to generate detailed test reports that can provide insights into the test results (e.g., pass/fail status, execution time). - Implement logging mechanisms (e.g., using Log4j, SLF4J) to capture test execution logs for easier debugging. - Setting Up Data Management: - Ensure that the framework handles data setup and teardown for test cases efficiently. This could mean using mock data, data-driven tests, or creating data before running tests and cleaning it up afterward. - Create reusable test data sets (e.g., using CSV, Excel, JSON) or integrate with databases to fetch dynamic test data as needed. - Integrating with CI/CD: - Set up the automation tests to run automatically in your CI/CD pipeline whenever code changes are pushed to version control (e.g., using Jenkins pipelines or GitHub Actions). - Ensure that your framework is integrated with version control systems like Git so that automated tests can track and execute based on changes in the codebase. - Test Execution and Parallelization: - Configure the framework to run tests in parallel (if needed) to save time, especially for large test suites. Tools like TestNG (with Selenium) or JUnit support parallel test execution. - Use grid services (e.g., Selenium Grid, BrowserStack, or Sauce Labs) to run tests across different environments and browsers. - Scalability and Maintenance: - Ensure that the framework is scalable and can be extended easily as new tests or features are added. Modularize test components like test steps, libraries, and utilities to avoid code duplication and simplify maintenance. - Create proper documentation for the framework so new team members can easily onboard. - Review and Iterate: - After setting up the automation framework, continually review and improve it based on test results, performance, and team feedback. - Regularly refactor the framework to optimize performance, reduce flakiness, and add new capabilities.

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Software quality is the degree to which software meets specified requirements, is reliable, maintainable, and satisfies user needs.

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A traceability matrix also known as Requirement Traceability Matrix(RTM) is a document that is used in the development of the software application to trace the requirements proposed by the client to the system being built. Some of the features of RTM are- - It is prepared before test execution to make sure that all the requirements are covered in the test cases. - The test engineers will prepare RTM for the respective assigned modules. - These will be submitted to the Test Lead. - The Test Lead will verify the specific module RTM to see if all the requirements of that module are mapped to corresponding test cases and in the end, will consolidate all the RTMs and prepare one necessary RTM document. - The main purpose of RTM is to check that all requirements are checked via test cases. Read More – Traceability Matrix.

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At Infosys, I noticed our testing cycle was causing significant delays. I introduced a shift-left testing strategy, integrating testing earlier in the development process. By training developers on testing best practices and using automated testing tools, we decreased the defect rate by 30% and shortened the testing cycle by 20%. This initiative not only improved product quality but also fostered a culture of quality across teams.

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I'd first reproduce the bug consistently to make sure it's not a one-off fluke. Once I've confirmed it, I'd document it in our bug tracking system with: a clear title describing the issue, the exact steps to reproduce it, the environment it occurred in (browser, OS, version), what I expected to happen, and what actually happened. I'd include screenshots or a screen recording if visuals help. Then I'd assign it the appropriate priority based on severity—critical if it breaks the app, high if it's a major feature, medium if it impacts functionality, and low for cosmetic issues. I'd also add relevant labels or components so the right developer sees it. Once it's logged, I'd notify the developer in Slack or during standup. For critical bugs, I'd reach out immediately. I've found that the more context I provide upfront, the faster developers can fix it. I've also learned to avoid phrases like ‘it's broken' and instead stick to observable facts.

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'Monkey testing' is a method for testing software where testers generate random inputs to assess the software's behavior. Random inputs can take several forms, such as generating several random keystrokes or button clicks to check which actions will cause the application to crash or produce errors. This process is handy if the software interacts with many inputs where it would be impossible to test all combinations with other methods.

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It is impossible to exhaustively test software or prove the absence of errors, no matter how specific your test strategy is. An extensive test that finds hundreds of errors doesn't imply that it has discovered them all. There could be many more errors that the test might have missed. The absence of errors doesn't mean there are no errors, and the software is perfect. It could easily mean ineffective or incomplete tests. To prove that a program works, you'd have to test all possible inputs and their combinations. Consider a simple program that takes a string as an input that is ten characters long. To test it with each possible input, you'd have to enter 2610 names, which is impossible. Since exhaustive testing is not practical, your best strategy as a tester is to pick the test cases that are most likely to find errors. Testing is sufficient when you have enough confidence to release the software and assume it will work as expected.

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With software testing, testers aim to fix errors they notice during the testing process, while QA sees testers focus on preventing mistakes from happening in the first place. QA ensures the software complies with every specification, and testing involves checking the product's flaws. Software testing happens after developers write the code and quality assurance happens in the software development phase.

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Manual testing refers to the process of testing software manually, without the use of automation tools. Testers execute test cases and evaluate the functionality of the software, checking for issues, defects, or discrepancies between the expected and actual behavior. In manual testing, testers take on the role of end users, verifying whether the software meets the specified requirements and behaves as expected. They also check user interactions, user interfaces, workflows, and other aspects that may not be easy to automate. The process involves: - Test Case Design: Testers create detailed test cases based on functional and non-functional requirements. - Test Execution: Testers manually execute these test cases, interacting with the application in a variety of ways to check its behavior. - Defect Reporting: When testers encounter issues, they document the defects in a defect management tool and provide detailed information to the development team for resolution. Manual testing is often preferred in situations where automation isn't feasible or cost-effective, such as testing for usability, ad-hoc testing, or exploratory testing. However, it is also time-consuming and prone to human error, which is why it is often supplemented with automated testing for larger or repetitive projects.

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How much testing a software needs depends on its complexity. This helps determine the level of testing required. The interviewee should be able to provide a basic explanation of the concept of cyclomatic complexity and preferably display knowledge of nodes, edges, and calculating cyclomatic complexity for a piece of software.

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A Requirement Traceability Matrix, or RTM for short, is a document that matches test cases with custom requirements. A RTM is usually presented in the form of a table and contains all user requirements and artefacts from the project.

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Your interviewee should be able to approach QA from a proactive and preventive standpoint. With this premise, look for an answer that includes improper allocation of resources, scheduling issues, lack of attention to detail, and deviation from the overall test strategy established at the outset.

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Test coverage measures how much of your test cases are covering application code. A good test coverage goal is 80%, as any more than this could be costly without much additional benefit. To calculate test coverage, you will need to determine how many requirements there are, how many tests are created and how many are executed. A test coverage tool will measure how much of the programme's source code is covered as a percentage. There are a few different types of test coverage techniques, such as block, brance, path and function. You should be able to give a top-level description of these, in case it comes up during your interview.

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This is an important subject to focus on while prepping for QA interview questions because it shows that you understand the principles that undergird this work. You should cover the following areas in your answer: - Objectives - Scope - Environment - Testing the frame - The reasons driving your testing - Risk factors - Deliverables - Criteria for entrance/exit

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I focus on core user flows and clarify assumptions early.

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There are two main types: - Manual Testing - Exploratory Testing - Black Box Testing - White Box Testing - Ad-hoc Testing - Automation Testing - Unit Testing - Integration Testing - Regression Testing - Performance Testing For an in-depth comparison of Manual Testing vs. Automation Testing, explore DevAssure's comprehensive guide by clicking the hyperlink above. This resource provides valuable insights to help you understand the key differences, advantages, and best use cases for both testing approaches.

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I rely on data, reproduction steps, and user impact instead of opinions.

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Decision table testing is used when business rules have multiple conditions and combinations. It represents conditions and actions in a table format to cover all possible rule combinations. It is useful for complex IF-THEN-ELSE logic like insurance premium calculation based on age and health factors. It helps avoid missing combinations that equivalence partitioning may not cover. It is best used when business logic is rule-heavy and condition-based.

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- Load Testing: Simulates expected user load to check performance. - Stress Testing: Pushes the system beyond its limits to check stability.

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All web applications run in browsers such as Google Chrome, Mozilla Firefox, Internet Explorer, Safari, etc. Though they all work primarily the same in implementing the web standards, there are subtle differences in all of them. When building the software, it's not always possible for the software developer to meticulously test the feature on multiple browsers, noticing the subtle inconsistencies. In cross-browser testing, a software tester launches the web application in all the supported browsers and tries to test the same functionality on all of them. They note any unexpected behavior in a browser that doesn't work as expected or looks different; note the behavior and the browser name and version in the test report. This helps the programmer to fix the behavior in all the browsers where it doesn't work as intended.

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There is no right or wrong answer here. The goal of this question is to assess if the person is familiar with various tools needed to perform testing. You can even mention certification you've completed that may be relevant.

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Deciding whether to automate a test case is critical to ensure efficiency and effectiveness. The following factors influence this decision: - Repetitiveness: If a test needs to be executed frequently, especially for regression testing, automation is beneficial. Repetitive tests (e.g., login, user registration) are prime candidates for automation. - Test Stability: Automating tests that are stable and unlikely to change frequently reduces maintenance overhead. If a test case is still evolving or prone to frequent changes, automation may not be worth the initial investment. - Test Complexity: Automation is ideal for complex test cases involving multiple steps, interactions, or large data sets. For simple test cases, manual testing may be more efficient. - Critical Business Functions: High-priority features that are critical for business operations, such as payment processing or login functionality, should be automated to ensure consistent and thorough testing. - Resource Availability: Automation requires resources like skilled automation engineers, tools, and time. If these resources are available and the cost is justified, automation makes sense. - Test Coverage: For large applications, automating tests can help ensure broader test coverage, especially for cross-browser or multi-platform testing, where manual testing can be time-consuming. - Execution Time: If a test suite takes too long to execute manually, automating it can speed up the process. This is particularly relevant for performance or load testing, where running tests manually would be too slow. - Environment and Data Setup: Tests that require specific configurations, environments, or large sets of data benefit from automation, as automated tests can quickly reset the environment and run tests with fresh data. - Maintenance Effort: Consider the long-term maintenance of automated tests. If maintaining the scripts will be too complex or costly due to frequent application changes, it may not be worth automating. By evaluating these factors, you can determine whether automation will improve the overall efficiency and effectiveness of the testing process.

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Manual testing is crucial for testing software applications more thoroughly. The procedure of manual testing comprises of the following. 1. Planning and Control 2. Analysis and Design 3. Implementation and Execution 4. Evaluating and Reporting 5. Test Closure activities

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A bug is an error, flaw, or fault in a software application that causes it to produce incorrect or unexpected results, or to behave in unintended ways.Bugs can occur due to various reasons such as coding mistakes, incorrect algorithms, or overlooked requirements. Identifying and fixing bugs is crucial for ensuring the software's functionality, performance, and user satisfaction.

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When testing APIs that lack documentation, I would thoroughly test the API with various combinations and permutations. - Use tools like Swagger or Postman to inspect API response headers & response body. - Look for developer comments and schema definitions. - Reverse-engineer fields such as data types and validation rules to analyze the working of the API. - Ask developers for minimal contract details. - Test using typical, edge, and negative inputs.

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Although branch and boundary testing sounds similar, they address different aspects of application testing. With branch testing, you test the different branches of code. On the other hand, boundary testing involves testing the limit conditions of an application.

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A sprint is a set period during which specific tasks or features are developed and tested. Sprints are typically 2-4 weeks long.

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Grey box is the combination of both White Box and Black Box Testing. The tester who works on this type of testing needs to have access to design documents. This helps to create better test cases in this process.

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Use the STAR method to describe a hypothetical situation in which you have doubts about a project, the tasks you'd be responsible for, the actions you'd take to communicate your doubts or find out more through research, and the results you would anticipate. Take the opportunity to emphasize your critical thinking and communication skills, as well as your conscientious approach to understanding a project inside and out.

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Software testing is the process of evaluating an application to ensure it meets the desired requirements and is free of bugs that could affect users. The goal of software testing is not just to find bugs, but to verify that the system remains stable under various conditions, reducing the risk of failures before it's released for users.

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In CD pipelines, testing is automated and integrated into the build process. Automated tests (unit, integration, regression) are run continuously as part of the deployment pipeline to ensure that code is production-ready at any time.

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Defect handling is key for software checks. You should describe how you track, log, and fix bugs. Mention tools for bug tracking and note how talking to coders is crucial.

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The defect, or big, lifecycle follows all the stages a bug goes through. Starting as a new bug when first detected, to ultimately being resolved. The defect life cycle steps are as follows:

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Defect life cycle, also known as a bug life cycle, is a life cycle of various stages through which a defect goes during its whole lifetime. This life cycle starts as soon as the defect is discovered or reported by the tester and ends when the tester ensures that the defect is resolved and it won't occur again. The defect life cycle includes the steps as shown below:

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First, I gather exact steps, browser, OS, screenshots, timestamp, and user details. Then I check server logs and error monitoring tools for that time. I try to match the same environment including browser version, network speed, and data state. I test variations like different roles, data sets, or concurrent actions to detect race conditions. If still not reproducible, I add extra logging and keep stakeholders updated with findings and risk status.

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Specific considerations can help teams decide when to stop testing, including: checking if testers have met the release or testing deadline, taking note of the test case pass rate, determining if the project's risk level is lower than the level permitted, considering if the team has removed the important bugs, and seeing whether the application meets the specifications or requirements.

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If I have only one day for testing a story, I would follow the steps below: - Break the story into testable pieces so that each piece can be tested efficiently and effectively. - Perform parallel testing while the developer finishes tasks. - Focus on the happy path first with valid inputs to ensure the basic feature works. - Automate sanity checks to speed up testing. - Use exploratory testing for coverage optimization.

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Author, Moderator, Reviewer(s), Scribe/Recorder and Manager.

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It's a process of automatically testing a web application's functionality in a browser, where a program launches the browser, navigates to the application, and interacts with the user interface by clicking buttons or links, just like an average user would. The only difference is that the browser automation can test this very quickly and often, whereas the same test would take a human tester a long time. It's part of automated testing. Some essential tools for browser testing include Selenium, protractor.js, and cypress.

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We can do System Testing only when all the units are in place and working properly. It can only be done before User Acceptance Testing (UAT).

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Software development testing is a collaborative process that requires teamwork. Instead of treating testing as a separate phase, it works well when QA is involved during requirement discussions or design reviews. For instance, discussing testability upfront can prevent many automation challenges later. Also, regular communication helps when debugging failures, as developers can provide quicker insights into code-level issues.

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Integration Testing vs System Testing | INTEGRATION TESTING | SYSTEM TESTING | |---|---| | It is a low level testing | It is a high level testing | | It is followed by System Testing | It is followed by Acceptance Testing | | It is performed after unit testing | It is performed after integration testing | | Different types of integration testing are: • Top bottom integration testing • Bottom top integration testing • Big bang integration testing • Sandwich integration testing | Different types of system testing are: • Regression testing • Sanity testing • Usability testing • Retesting • Load testing • Performance testing • Maintenance testing | | Testers perform functional testing to validate the interaction of two modules | Testers perform both functional as well as non-functional testing to evaluate the functionality, usability, performance testing etc., | | Performed to test whether two different modules interact effectively with each other or not | Performed to test whether the product is performing as per user expectations and the required specifications | | It can be performed by both testers and developers | It is performed by testers | | Testing takes place on the interface of two individual modules | Testing takes place on complete software application | | Here, we validate the interace between the individual modules. | Here, we validate the finished product. | | Testers need to understand the interlinked modules and their interaction. | Testers need to understand the internal structure and programming language. | | It covers only functional testing. | It covers both functional and non-functional testing. |

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Load testing verifies how a system behaves under expected and peak load conditions, while performance testing assesses speed, responsiveness, and stability. Both are crucial for ensuring software scalability.

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The top 7 qualities of Software Developers are: - Technical Expertise: A developer must have strong technical expertise so that he/she knows how to achieve an optimal solution for a particular task. Their code will not be clear and understandable but also follow the coding standards. - Maintains an End-User Focus: An exceptional developer will want to first fully understand the business case for the major projects they undertake. This is to ensure that their actions will not only affect the end-users but ultimately the organization. - Ability to Learn, Grow, and Adapt: Continuous improvement is a good practice for both the software and the engineer. - Time Management: A software developer must be a master at managing their time in order to cram so much action into every single working day. - Interpersonal Skills: Some of the key interpersonal skills that a software engineer needs are Collaboration skills, Communication skills, Empathy skills, Critical thinking skills, and Leadership skills. - Communication Skills: A good developer must know how to communicate, clarify, explain, and persuade. - Curiosity: Good developers are inquisitive. They tend to ask themselves and their peer a lot of questions while they work. - Good Team Player: A good developer shares their knowledge and believes in upscaling their team. They offer teammates help when they face problems that they cannot solve.

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'Build' in quality assurance refers to converting source code into software artifacts. Developers or testers can run these artifacts, which are typically versions of programs that customers can use. Testers can test each build if they don't satisfy the requirements before release. Several builds contribute to one release.

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Bug/Defect severity can be defined as the impact of the bug on customer's business. It can be Critical, Major or Minor. In simple words, how much effect will be there on the system because of a particular defect.

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Globalization Testing ensures software works across various regions without localization.

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Defect reporting is the process of documenting and tracking issues (bugs) that are discovered during testing. A well-defined defect reporting process ensures that defects are communicated clearly to the development team and resolved efficiently. The key steps in defect reporting include: - Defect Identification: When a defect is found, the tester should first confirm the issue. This involves reproducing the defect, verifying the severity, and ensuring that it's not caused by an error in the test environment or by misinterpreting the requirements. - Defect Documentation: The tester records detailed information about the defect, which usually includes: - Defect ID: A unique identifier for the defect. - Title: A brief description of the issue. - Description: A detailed explanation of the defect, including how it was found and any relevant information such as screenshots, logs, or steps to reproduce. - Severity: The impact of the defect on the system (e.g., critical, major, minor). - Priority: The urgency with which the defect needs to be fixed (e.g., high, medium, low). - Environment: The test environment where the defect was observed (e.g., operating system, browser version, hardware configuration). - Steps to Reproduce: Clear and precise steps to recreate the defect. - Expected vs. Actual Results: What the system should have done versus what actually happened. - Defect Assignment: After the defect is documented, it's assigned to the appropriate developer or development team for further analysis and resolution. - Defect Verification: Once the developer fixes the defect, the tester verifies the resolution by retesting the issue to ensure that the defect is resolved and that no new issues were introduced. - Defect Closure: If the defect is resolved and verified, the defect report is marked as closed. If the issue remains unresolved or if new defects are identified, the cycle continues. - Defect Tracking: Throughout this process, the defect is tracked using a defect management tool (e.g., JIRA, Bugzilla), ensuring that the issue is monitored until resolution. Effective defect reporting ensures clear communication between QA and development teams, enabling timely and accurate resolutions.

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