Top 25 Functional Testing Interview Questions

Entering the world of software testing might feel like navigating uncharted waters, but fear not! Functional testing, a cornerstone of software quality, is here to ensure applications run smoothly. Whether you’re stepping into the field or have an experienced hand, we’ve compiled a list of the top 25 functional testing interview questions for 2023. 

Let’s embark on this journey, combining practical analogies and technical depth for a successful interview.

Functional Testing Interview Questions for Freshers:

1. What is Functional Testing? 

Functional testing checks if software behaves according to its requirements and works as anticipated. It ensures that the application’s functions work in accordance with design documents. 

In functional testing, testers go through every feature of the software, like buttons, forms, and links, to make sure they perform as they are expected to. For instance, they check that buttons are clickable, forms can be filled out, and links take users to the right places. 

If anything doesn’t work the way it’s expected to, it’s identified as a “bug” or a problem that needs to be fixed. The aim is to guarantee that users encounter no issues and enjoy a seamless experience while using the software. 

2.Why is Functional Testing Important?

Functional testing directly influences user satisfaction by making sure that the software works as it should. Users expect applications to work smoothly, and functional testing ensures a positive user experience by catching and rectifying issues before they reach users.

Moreover, functional testing assures the quality and reliability of the software, aligning it with specified requirements and industry standards. This quality assurance not only establishes trust with customers but also helps in cost-effectiveness.

3.What are Different Types of Functional Testing?

Here are brief explanations of a few different types of functional testing:

Unit Testing: Unit testing involves checking individual components or functions of the software To confirm their proper functioning when tested individually. 

Integration Testing: Integration testing concentrates on validating how different parts or sections of the software collaborate. It ensures that when these pieces interact, they do so seamlessly, preventing integration-related bugs.

System Testing: System testing assesses the complete software system as a single unit. Testers assess the application’s behavior and functionality across various scenarios, mimicking real-world usage to identify any issues that might arise during actual user interactions.

User Acceptance Testing (UAT): UAT involves actual users testing the software to verify it aligns with their needs and expectations It’s the final validation that the software aligns with the users’ needs before it’s released.

Regression Testing: Regression testing ensures that new changes or updates to the software haven’t introduced new issues or broken existing functionalities. 

Smoke Testing: Smoke testing is a quick, high-level check to ensure that the most critical functions of the software are working without major issues. 

Sanity Testing: Sanity testing focuses on specific areas or functionalities of the software after a change or update. 

4.How is Functional Testing Performed?

Functional testing involves several key steps:

Test Planning: The first step is to plan the functional tests. Testers work with project stakeholders to define test objectives, scope, and requirements. They create a test strategy that outlines the testing approach, the features to be tested, and the testing environment.

Test Case Design: Testers create detailed test cases based on software requirements. These test cases outline specific actions to be performed, including inputs, expected outputs, and any preconditions or prerequisites.

Test Execution: Testers execute the prepared test cases. This involves interacting with the software by clicking buttons, entering data, and following predefined workflows. Testers systematically go through each test case, documenting the results.

Defect Reporting: When testers encounter issues during test execution, they report these defects to the development team using a standardized format. The defect reports provide details about the issue, instructions to recreate it, and its level of seriousness.

Regression Testing: After developers fix reported defects, regression testing is performed. This involves retesting the affected areas to ensure that the fixes did not introduce new issues or impact other functionalities.

Test Reporting: Testers compile test results and create test reports. These reports detail the outcomes of the tests, including any defects found, their severity, and whether the software meets the defined criteria.

Test Closure: Once all test cases have been executed, and defects have been addressed, a test closure report is prepared. This report summarizes the testing process, including achievements, issues, and recommendations for future testing efforts.

Automated Testing (Optional): In some cases, functional testing can be automated using testing tools and scripts. Automated tests speed up testing, especially for repetitive tasks and regression testing.

Continuous Improvement: After testing is complete, the testing team and development team collaborate to analyze the results and identify areas for improvement. Lessons learned from testing are used to enhance the software’s quality and development processes.

5.Difference between Functional and Non-Functional Testing?

Functional testing validates the application’s software features and functions, while non-functional testing focuses on aspects like performance, security, and usability. While functional testing checks if all buttons on a TV remote work, non-functional testing explores how quickly the TV responds to commands.

Aspect	Functional Testing	Non-Functional Testing
Focus	Core functionality and features	Performance, reliability, and other attributes beyond core functionality
Test Criteria	Predefined test cases based on functional specifications	Assessment of qualitative aspects, often without predefined test cases
Examples	Button functionality, form submissions, calculations, navigation	Load testing, security testing, usability testing
Pass/Fail	Typically has clear pass/fail criteria	Relies on metrics, benchmarks, and acceptable ranges
User-Centric	Primarily user-centric, ensuring software functions as expected by users	System-centric, evaluating how the software operates under different conditions
Objective	Verify that software performs its intended functions correctly	Assess various attributes that contribute to the overall user experience
Outcome	Focused on correctness and adherence to requirements	Focused on performance, security, and usability, among others

6.Explain Unit Testing vs. Functional Testing

Unit testing tests individual units or components of code, while functional testing evaluates the application’s complete functionality. Unit testing resembles tasting individual ingredients before cooking, while functional testing is like savoring the entire dish.

Aspect	Unit Testing	Functional Testing
Focus	Individual components or functions	Entire software application
Test Scope	Highly specific, one component	Broad, multiple components/features
Isolation	The component under test is often isolated	Interaction between components is considered
Development Stage	Typically performed during development by developers	Typically performed during the QA phase by dedicated testers
Automation	Commonly automated, part of continuous integration	Automation is used but manual testing is also common, especially for UI
Purpose	Ensure the correctness of small code units	Validate overall software functionality from an end-user perspective
Example	Testing a single function or method	Testing the entire application, including user interactions

7.What is Functional Testing vs. Regression Testing?

Functional testing ensures each function works correctly, while regression testing verifies that new changes don’t negatively impact existing functionalities. 

Aspect	Functional Testing	Regression Testing
Focus	Core functionality and features	Ensuring existing features still work
Test Criteria	Predefined test cases based on functional specifications	Primarily retesting of previously validated features
Examples	Button functionality, form submissions, calculations, navigation	Rechecking login, data storage, and existing features
Pass/Fail	Typically has clear pass/fail criteria	Primarily focuses on identifying regressions (failures)
Objective	Verify that software performs its intended functions correctly	Make sure that new changes haven’t broken existing code functionality
Timing	Conducted during development and quality assurance phases	Often performed during regression test cycles before software releases
Automation	Automation is used but manual testing is also common, especially for UI	Automation is common and integral to frequent regression testing
Changes Considered	Focuses on new features or changes being tested	Recheck existing features after changes to detect unexpected problems

8.Explain Adhoc Testing

Adhoc testing involves unplanned and random testing to identify defects that might not be overlooked by formal test cases. Adhoc testing mirrors exploring a new city without a map – you’re trying out random spots to uncover hidden gems.

Here’s a breakdown of adhoc testing:

Exploratory Approach: Testers explore the software application without a specific script or set of instructions. They interact with the software as end-users might, trying various actions and inputs to identify unexpected behaviors or defects.

Unscripted Tests: Testers perform unscripted tests, trying different scenarios and actions that are not necessarily documented in any test plan. They might click on elements out of sequence, enter unusual data, or use the software in unexpected ways.

Error Discovery: The primary goal of adhoc testing is to discover defects, errors, or unexpected behaviors that might not be found through scripted testing. Testers aim to uncover issues that might emerge during real-world usage.

Limitations: Adhoc testing might not be suitable for comprehensive test coverage, especially for critical or regulated industries. Structured testing methods are essential for ensuring complete coverage and meeting specific compliance requirements.

9.How Does ‘Build’ Differ from ‘Release’?

A build is a version of the software, while a release is the distribution of a stable version to users. Think of a build as a blueprint for a cake, while a release is an actual cake presented to everyone at a celebration.

Aspect	Build	Release
Definition	A version of the software compiled from the source code, representing a specific point in time	A stable and well-tested version intended for distribution to end-users or customers
Scope	Generated frequently during development, may contain ongoing changes and updates	Infrequent, occurs at defined points in the development lifecycle, represents a milestone
Purpose	Primarily for internal development and testing, allowing developers to test code changes	Intended for external stakeholders, including end-users, customers, or clients, for production use
Testing	Testing includes unit testing, component testing, and sometimes integration testing	Comprehensive testing, including functional testing, regression testing, user acceptance testing, and performance testing
Stability	Less stable, may contain bugs or incomplete features, as it’s in active development	Stable and free from critical defects, considered production-ready
Scope of Changes	Can include several changes, from minor code edits to major feature additions	Includes a well-defined set of changes, often organized into release notes, thoroughly tested and verified

10.Difference between Monkey Testing and Adhoc Testing?

Monkey testing involves randomly clicking through an application, while adhoc testing is more structured and focuses on specific scenarios. Monkey testing is like letting a curious monkey explore your kitchen, while adhoc testing is more structured, like allowing an adventurous child to explore with guidelines.

11.State Difference between Alpha and Beta Testing?

Alpha testing is done by internal teams, while beta testing involves external users before public release. Alpha testing is conducted before beta testing. Alpha testing is inviting close friends to sample your new recipe, while beta testing involves inviting neighbors to taste and provide feedback.

Aspect	Alpha Testing	Beta Testing
Timing	Conducted before Beta Testing	Conducted after Alpha Testing
Purpose	To identify defects and issues within the organization before releasing to external users	To gather user feedback, evaluate real-world performance, and uncover issues in a controlled external environment
Participants	Internal teams, often developers and testers	External users or a selected group of customers
Scope	Limited scope, typically focusing on core functionalities	Wider scope, encompassing various user scenarios and real-world usage
Environment	Testing usually occurs in a controlled, non-production environment	Testing occurs in a real or simulated production environment
Focus	Internal quality assessment and defect identification	Real-world user experience, feedback collection, and validation of product readiness
Control	The organization has more control over the testing process and environment	Less control over external users’ actions and environments
Goals	Confirm the software works correctly and meets internal standards	Collect user feedback, assess usability, and validate the product’s readiness for public release
Duration	Generally shorter duration compared to Beta Testing	Typically a longer testing phase, allowing for more extensive user interactions
Scope of Changes	Alpha versions may still undergo significant changes based on internal feedback	Beta versions are more stable and represent near-final product versions
Feedback Utilization	Feedback primarily influences internal development and refinement	Feedback drives final product improvements and fixes for the external release
Confidentiality	Often conducted under non-disclosure agreements to maintain confidentiality	Involves external users who may not be bound by non-disclosure agreements

12.What are Different Test Techniques Used in Functional Testing?

Functional testing techniques include equivalence partitioning, boundary value analysis, and decision table testing for comprehensive validation. Think of test techniques as various ways to check if a cake is perfectly baked – poking it, smelling it, slicing it.

Here are some common test techniques used in functional testing:

Black Box Testing: This technique focuses on testing the software’s functionality without considering its internal code structure. Testers validate whether the software meets specified requirements and produces expected outputs based on various inputs.

White Box Testing: White box testing examines the internal code and logic of the software. Testers assess how well the code functions, including branch coverage, path coverage, and code execution paths.

Equivalence Partitioning: Equivalence partitioning involves dividing input data into equivalent classes or partitions and testing representative data from each partition. It helps ensure that the software handles different input scenarios effectively.

Boundary Value Analysis (BVA): BVA complements equivalence partitioning by focusing on the boundary values of input partitions. Testers assess how the software behaves at the edges or limits of input ranges, as these often lead to defects.

State Transition Testing: State transition testing is suitable for systems with distinct states. Testers evaluate how the software transitions between different states and whether it performs actions correctly in each state.

Exploratory Testing: Exploratory testing is an unscripted, adhoc approach where testers explore the software, identify issues, and learn about its behavior. It’s valuable for uncovering defects and assessing overall user experience.

Concurrency Testing: Concurrency testing evaluates how the software handles multiple users or processes simultaneously. It’s essential for applications with multi-user support to ensure that concurrent interactions do not lead to data corruption or conflicts.

Compatibility Testing: Compatibility testing assesses how the software performs on different devices, browsers, or operating systems. It ensures that the software functions as expected across various environments.

These test techniques, when used appropriately, contribute to comprehensive functional testing. This helps ensure that the software meets its requirements, functions correctly, and delivers a positive user experience.

13.Explain Risk-Based Testing and its Important Factors

Risk-based testing prioritizes test cases based on potential risks, considering critical functionalities and business impact. It focuses on potential pitfalls. Imagine risk-based testing as making sure the dessert is flawless before the main course.

Risk-based testing is a testing approach that places a primary focus on mitigating the most critical and impactful risks to software quality and functionality. The key to effective risk-based testing lies in several critical factors:

First and foremost, Risk Identification is paramount. Teams need to accurately identify risks associated with the software, which can range from technical complexities to business impact and compliance issues. This often requires collaboration across different domains and expertise areas.

After identifying risks, the next action involves conducting a Risk Assessment. Teams evaluate each risk’s potential impact and likelihood. 

Risk Prioritization is next. Risks are categorized into high, medium, and low priority based on their assessment. High-priority risks are those with the most significant potential impact on the project’s success.

The testing strategy is then adjusted to align with these priorities. Test Strategy and planning involve designing test cases and scenarios that specifically target high-priority risks. These test cases receive a higher degree of attention in the overall testing strategy.

Resource allocation is also crucial. Resource Allocation ensures that more resources, including time, budget, and testing personnel, are directed toward mitigating high-priority risks, while lower-priority risks may be addressed in subsequent testing phases.

To effectively address high-priority risks, the Test Coverage is aligned with these priorities. This means that high-priority areas receive more extensive testing, ensuring that the most critical aspects of the software are thoroughly validated.

During the Test Execution phase, close monitoring of identified high-priority risks is essential. Should defects or issues be found in these areas, they are addressed urgently to mitigate potential negative impacts.

Maintaining a Feedback Loop is integral. Continuous communication and feedback loops with stakeholders help in adapting the testing approach as the risk landscape evolves. This ensures that the testing process remains aligned with the project’s changing priorities.

Documentation plays a vital role in risk-based testing. Clear and comprehensive documentation of Risk Assessments, Prioritization, and Test Plans provides transparency and accountability throughout the testing process.

Regression Testing becomes especially important in risk-based testing. As new risks are identified and mitigated, regression testing ensures that previously tested areas remain stable.

The adaptability of the testing approach is key. It should be able to accommodate Changing Project Circumstances and Priorities, as new risks may emerge or the risk landscape may evolve over time.

Finally, alongside testing, it’s essential to have in place Risk Mitigation Strategies. These strategies could involve risk avoidance, risk acceptance, or detailed risk mitigation plans to address high-priority risks effectively.

14.What is the difference between a “build” and a “release” in functional testing?

In the context of functional testing, “build” and “release” are versions of the software as they exist at different stages of the SDLC.

• The build is the software version at any point of the SDLC, before its release. This version is compiled and ready for tests. Often, multiple builds are created throughout the project, each with new features or resolved bugs.
  
  Each build is tested to check the veracity of the new code. It passes if the code is defect-free.
  
• The release is the software version actually deployed to end users. It has been verified with a series of tests, and hits the market for its target audience. Releases occur far less frequently than builds. 

15.What is a critical bug in functional testing?

In functional testing, “critical bug” refers to any defects that adversely impact the core functionality of the software under test. Such bugs will render the app unusable by end-users, and is a major bottleneck in business value. 

Examples of critical bugs in functional tests are application bugs, data loss, data corruption, security gaps and system instability. 

To decide if a bug qualifies as critical, it must be:

• Severe enough to significantly disrupt user experience. 
• Occur frequently and affect a large number of the app’s users. 
• Consistently reproducible so it is easy to find and fix. 
• Interfering with the software’s business value and goals. 

16.What is a testbed?

A testbed is essentially the test environment i.e., the setup for actually running the tests. It includes all the hardware, software, network configurations, and data necessary to run tests. The ideal testbed replicates the production environment as closely as possible. 

Essential components of a usable testbed:

• The software being tested. 
• Servers, workstations, network routers, peripheral devices like printers and other hardware.
• All OS versions chosen for testing the software. 
• Databases with appropriate test data. 
• Network configuration with IP addresses, network topology, and security settings. 
• Test management tools, automation tools and debugging mechanisms.
  

17.List a few indicators of a “good” test case. 

A good test case should be:

• Clear and concise, written in no-frills language and immediately understandable. 
• Specific to a single functionality or requirements. Each test case should ideally address a single requirement or feature. 
• Detailed and with logical steps that can be executed without additional context. 
• Reusable across different tests and scenarios. 
• Stands independent without depending on the outcome of test cases. 
• Traceable, i.e., clearly linked to a requirement or user story. 
• Structure to be run via automated tools. 

18.Explain the difference between bug release and bug leakage. 

Bug release and bug leakage are terms to indicate conditions in which software bugs escape into production, and show themselves hindering with the released product. 

When testers say “bug release” they refer to a situation in which a bug is detected after the app has been released to end users. That means that bug slipped through all layers of testing and made it to the final stages. It reveals a critical weakness in the test pipeline. 

While some bugs (especially minor ones) will always escape to production, a high number of frequent bug releases indicates that the testflows must be restructured for high efficiency.

“Bug leakage”, on the other hand, includes any bug that stays unidentified during a certain phase of tests, but is found after it moves onto the next stage – say, from development to testing, or testing to release. In other words, it “leaks” to the next stage. 

A high number of bug leakages indicate that testers are failing to detect bugs at the right juncture. It indicates that they may require better training or that there is a failure in a specific stage of the SDLC. 

19.What are the primary issues that lead to failures of functional tests?

When running functional tests, it’s important to look out for the following issues that often compromise the efficacy of said tests.

• Insufficient test coverage: If the product is not properly covered by necessary tests, it will cause critical bugs to escape to production level and disrupt user experience. Tests must verify all core functionalities, features and user scenarios.
  
• Inadequate test environments: If the test environment does not closely mimic the production environment, test results cannot be considered valid. It is essential to run functional tests on real browsers and devices — the ones utilized by actual end-users. 

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• Inadequate test data: If the test data is insufficient or unrealistic, tests will overlook bugs in data validation, error handling and edge cases.
  
• Poorly defined test cases: Test cases must be clear, concise and unambiguous. If not, they will execute poorly and generate inconsistent results or miss bugs.
  
• Skill deficiencies: Certain functional tests, especially automated ones, need a certain level of skill on part of the tester. They have to create refined automation scripts, and use specific tools to execute these scripts. The lack of such skills will certainly derail testing efforts.
  

20.What is the PDCA cycle in functional testing?

The PDCA cycle stands for Plan-Do-Check-Act. It is a workflow for implementing continuous improvement into test cycles, which inevitably leads to improved software quality. 

• Plan (P): At this stage, plan the testing activities. Define objectives, develop test strategy, create test cases, specify inputs and expected outcomes and identify most probable risks.
  
• Do (D):  At this stage, execute the planned tests. Set up the test environment, run test cases according to plan, document all bugs/issues, maintain test data and track test progress.
  
• Check (C): At this stage, analyze the results and evaluate the overall health of the test pipeline. Find the ratio of passed to failed tests, and evaluate if test coverage is adequate. Study if test cases, plans, and processes can be improved.
  
• Act (A): At this stage, take corrective actions based on the findings from the previous stage. Fix detected bugs, update/refine test cases, adjust the test plan and address all weaknesses in the test flows. 

21.Define entry criteria and exit criteria for functional testing

Entry criteria refers to the conditions to be met before tests can begin. It sets up the ideal circumstances for tests to run quickly, effectively and comprehensively.

• A stable and testable build, free of compilation and build errors. 
• A test environment that has been properly set up and configured to mimic the production environment. 
• Realistic and adequate test data ready to be fed into the system.
• A set of test cases created, reviewed and approved for execution. 
• All necessary test tools, configured and available to testers. 
• Complete requirements documentation available to testers. 
• The right testers who have been trained and briefed to run tests. 

Exit criteria refers to the conditions to be met after functional tests have been completed. These verify that an adequate number and type of tests have been executed, and all significant bugs have been resolved.

• All planned test cases have been executed. 
• Pre-determined test coverage goals (% of tested requirements, lines of code tested) have been met. 
• All identified bugs have been documented, reported and ranked. 
• All test results approved and reviewed by the QA lead. 
• A clarified summary report mentioning test status, bug stats and test coverage%. 
• A formal sign-off from the testing team. 

Functional Testing Interview Questions for Experienced

22.Explain Equivalence Partitioning

Equivalence partitioning is a technique that categorizes input data into groups, reducing the number of test cases needed while still ensuring comprehensive test coverage. The primary goal of equivalence partitioning is to ensure comprehensive test coverage while avoiding redundant and unnecessary test cases. Here’s a concise explanation of this technique:

Imagine you have a software application that takes numerical input for a specific field, such as age. Equivalence partitioning would involve dividing the possible input values into groups or partitions based on their equivalence, meaning that input values within the same partition are expected to behave similarly in the software. Here’s how equivalence partitioning works:

Identify Input Ranges: Start by identifying the input ranges or domains. In the case of age, you might have input values ranging from 1 to 100.

Divide into Equivalence Classes: Divide these input values into equivalence classes or partitions. For example, you could create the following partitions:

• Partition 1: Age values less than 18 (considered minors).
• Partition 2: Age values between 18 and 65 (considered adults).
• Partition 3: Age values greater than or equal to 65 (considered seniors).

Select Test Cases: Now, instead of testing every possible age value from 1 to 100, you only need to select test cases from each equivalence class. For instance:

• Test Case 1: Age = 15 (from Partition 1)
• Test Case 2: Age = 35 (from Partition 2)
• Test Case 3: Age = 70 (from Partition 3)

Expected Behavior: You can expect that the software should behave consistently within each equivalence class. For example, for Partition 1, the software should handle minor age inputs appropriately, while for Partition 2, it should handle adult age inputs correctly.

By using equivalence partitioning, you efficiently cover a wide range of potential inputs without the need to test every single value. This technique helps you uncover defects or issues related to how the software handles input data while minimizing redundancy in your test cases.

Equivalence partitioning is particularly valuable when dealing with large input domains, such as dates, currency values, or user IDs, where testing every possible input value would be impractical. It ensures that the most critical scenarios are tested, enhancing the overall efficiency of the testing process.

23.What is Boundary Value Analysis?

Boundary Value Analysis (BVA) is a software testing technique that focuses on testing values at the boundaries or limits of input domains. It’s based on the observation that many defects in software systems occur near the edges of valid input ranges or at the boundaries between different equivalence classes. BVA is especially valuable in uncovering errors related to data validation and handling.

Here’s a concise explanation of Boundary Value Analysis:

Identify Input Ranges: Begin by identifying the valid input ranges or domains for a particular input field or parameter in the software. For example, if you’re testing a field that accepts positive integers from 1 to 100, the input domain is 1 to 100.

Select Boundary Values: In BVA, you focus on the boundary values of the input domain. These include the minimum and maximum values within the range and values immediately adjacent to them. For the example above, the boundary values would be 1, 100, 2 (just above the minimum), and 99 (just below the maximum).

Test Boundary Values: Create test cases using these boundary values. For the example:

• Test Case 1: Input = 1 (minimum value)
• Test Case 2: Input = 100 (maximum value)
• Test Case 3: Input = 2 (just above the minimum)
• Test Case 4: Input = 99 (just below the maximum)

Expected Behavior: The goal is to verify that the software handles these boundary values correctly. In this case, you want to ensure that it accepts values within the specified range (1 to 100) and rejects values outside that range. Additionally, you check that the software behaves appropriately at the extremes (minimum and maximum).

BVA helps uncover defects that might occur due to off-by-one errors, incorrect comparisons, or boundary-related issues in the software’s logic. It ensures that the software behaves as expected at the critical points of input domains, where errors are more likely to occur.

This technique is particularly useful in scenarios where precise data validation and handling are essential, such as financial applications, where incorrect calculations or data truncation can have significant consequences.

24.State Difference between Functional and Structural Testing

Functional testing validates functionality, while structural testing examines the internal implementation of the application, including code and architecture. 

Aspect	Functional Testing	Structural Testing
Focus	Evaluates external behavior and features.	Examines internal code structure and logic.
Viewpoint	Assesses software from a user perspective.	Analyzes software at the code and algorithm level.
Test Basis	Based on requirements and specifications.	Requires knowledge of the software’s internal structure.
Examples	Unit testing, system testing, user acceptance testing and integration testing.	Unit testing (for code paths), code coverage analysis, and control flow testing.

25.What is UFT (Unified Functional Testing)?

Unified Functional Testing (UFT), formerly known as QuickTest Professional (QTP), is a comprehensive software testing tool developed by Micro Focus. UFT is designed to automate testing for desktop, mobile, and API-based applications. It is widely used by software testing professionals and quality assurance teams to enhance the efficiency and effectiveness of their testing efforts.

26.What is Data-Driven Testing?

Data-driven testing involves executing the same test script with multiple data sets to ensure diverse scenarios are covered. 

The primary goal of data-driven testing is to validate that a software application behaves correctly and consistently across various input values. In data-driven testing, a test script or scenario is designed to accept input data from external sources, such as spreadsheets, databases, or text files. The test script remains the same, but the data used in the test varies. The data is fed into the test script, and the script is executed for each set of input data.

Example

Let’s consider a simple example of a login page for a web application. The goal is to test the login functionality with various username and password combinations to ensure that it works correctly for different user credentials.

Test Script: The test script for the login functionality is created. It includes steps to open the login page, enter a username and password, click the “Login” button, and verify the expected outcome (e.g., successful login or error message).

Data Preparation: Test data is prepared in an external data source, such as a spreadsheet. The data might look like this:

Username	Password
user1	pass1
user2	pass2
invalidUser	wrongPass
user3	pass3

Data-Driven Execution: The test script is configured to read data from the data source and execute the login test for each row of data. Here’s how the test execution would look:

• Test Case 1: Use “user1” as the username and “pass1” as the password. Verify successful login.
• Test Case 2: Use “user2” as the username and “pass2” as the password. Verify successful login.
• Test Case 3: Use “invalidUser” as the username and “wrongPass” as the password. Verify an error message is displayed.
• Test Case 4: Use “user3” as the username and “pass3” as the password. Verify successful login.

Results

The test execution results are recorded. This includes whether each test case passed or failed and any additional information or error messages captured during the test.

Benefits of Data-Driven Testing:

• Efficiency: Reduces the need to create separate test cases for each data combination.
• Coverage: Ensures that the software is tested with a wide range of input values.
• Reusability: The same test script can be reused with different datasets.
• Maintainability: Easy to update or add new test data without modifying the test script.

Data-driven testing is commonly used for scenarios like form submissions, data validation, and parameterized testing, where input data plays a crucial role in determining test outcomes.

27.Explain Smoke Testing and Sanity Testing

Smoke testing verifies basic functionalities after a build, while sanity testing validates specific functionalities after changes are made. Smoke testing checks if the cake is burnt immediately after baking. Sanity testing ensures the cake’s decorations look perfect.

Smoke Testing:

• Purpose: Smoke testing, also known as “build verification testing,” aims to ensure that the essential functionalities of the software or application are working correctly and that it is stable enough for further testing. The goal is to detect critical issues that could hinder further testing.
• Scope: Smoke tests cover the most crucial and basic features of the application. These tests are typically part of an automated or scripted test suite and focus on core functionalities.
• Execution Time: Smoke testing is executed after a new build or version of the software is deployed but before more comprehensive testing phases. It is a preliminary check and should not be time-consuming.
• Outcome: If the application passes the smoke test, it signifies that it’s stable enough to proceed with more extensive testing, such as regression testing, functional testing, and other testing phases. If it fails, it indicates significant issues that need immediate attention.

Sanity Testing:

• Purpose: Sanity testing, also known as “narrow regression testing,” is performed to verify that specific modifications or fixes in the codebase have not adversely affected the existing functionalities of the application. It focuses on specific areas of the application that were changed or areas directly related to those changes.
• Scope: Sanity tests are narrow in scope and target specific features or modules that have undergone recent changes. They are not intended to provide exhaustive coverage but rather to validate that the recent code changes did not break existing functionality.
• Execution Time: Sanity testing is executed after code changes, enhancements, or bug fixes have been implemented and retested. It helps ensure that the software is still working as expected after the modifications.
• Outcome: If sanity testing reveals no issues with the modified or impacted areas, it confirms that the changes did not introduce regression defects. If issues are identified, it indicates that further investigation and fixes are needed.

Key Differences:

• Scope: Smoke testing verifies basic application stability, while sanity testing focuses on specific, recently modified areas.
• Purpose: Smoke testing checks overall readiness for testing, while sanity testing confirms that specific changes haven’t adversely affected existing functionality.
• Execution Time: Smoke testing occurs before further testing phases, while sanity testing occurs after specific changes are implemented.

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28.What is RTM (Requirement Traceability Matrix)?

RTM is a document that connects project requirements to corresponding test cases, ensuring complete test coverage. Think of RTM as a master recipe, detailing all ingredients used – ensuring nothing is missing from your dish.

A Requirement Traceability Matrix (RTM) is a document used to maintain a clear link between the project’s requirements and the various stages of its development and testing lifecycle. It is essentially a table that maps each requirement to the corresponding design, development, and testing activities. In an RTM:

• Requirements are listed in one column. Other columns represent various phases of the project, such as design, development, and testing.
• Each cell in the matrix indicates whether a requirement is associated with or addressed in a particular phase. Common symbols or statuses like “Yes,” “No,” “In Progress,” or “Tested” are used to denote the relationship or status of each requirement in each phase.

The RTM serves as a valuable tool for project management, quality assurance, and testing teams. It provides transparency, helps track progress, and ensures that all project requirements are thoroughly tested and validated. When discrepancies or gaps are identified in the matrix, they can be addressed promptly to maintain the project’s alignment with its original requirements.

29.Why is RTM (Requirement Traceability Matrix) Important?

RTM ensures that all requirements are tested and that no functionality is missed during testing. It provides a roadmap for testing. RTM ensures all required ingredients are in place before you start cooking – no missing spices!

A Requirement Traceability Matrix (RTM) is important in software development and testing for several key reasons:

• Requirement Alignment: It ensures that project requirements align with the design, development, and testing activities. By mapping requirements to specific phases, it helps maintain the project’s focus on meeting customer needs and project objectives.
• Completeness Check: RTM serves as a checklist to verify that all specified requirements have been addressed. It helps identify any gaps or omissions in the requirements documentation, ensuring that nothing is missed during development and testing.
• Change Management: When requirements change or evolve throughout a project, the RTM helps assess the impact of these changes. It allows project stakeholders to see how modifications affect various phases and adjust their plans accordingly.

• Risk Mitigation: By tracing requirements through different phases, the RTM helps identify potential risks early in the development process. It allows project managers and testers to focus their efforts on high-priority areas, reducing the likelihood of critical issues going unnoticed.
• Test Coverage: For testing teams, the RTM provides a clear understanding of which requirements need to be tested and to what extent. It ensures that test cases are designed to cover all necessary scenarios and that there is no redundancy in testing efforts.
• Validation and Verification: The RTM facilitates the validation and verification of requirements. It enables testers to confirm that each requirement has been correctly implemented and that the implemented functionality aligns with the original specifications.
• Reporting and Documentation: RTM serves as documentation that can be shared with stakeholders, auditors, and regulatory bodies to demonstrate compliance with requirements. It provides a transparent record of how each requirement has been addressed throughout the project.
• Efficiency and Accountability: It enhances efficiency by streamlining communication and reducing misunderstandings between different project teams. Each team can see their responsibilities and accountabilities about the requirements.
• Quality Assurance: By ensuring comprehensive requirement coverage and traceability, RTM contributes to the overall quality of the software product. It helps deliver a product that meets or exceeds customer expectations.
• Project Control: RTM provides project managers with a tool for monitoring progress. It allows them to track which requirements have been addressed and which are pending, enabling better project control and resource allocation.

30.Difference between Retesting and Regression Testing?

Retesting verifies if a specific defect has been fixed, while regression testing prevents new changes from affecting existing functionalities. Retesting is like tasting a dish again to ensure the issue is resolved. Regression testing checks if changing an ingredient affects the overall taste.

Aspect	Retesting	Regression Testing
Purpose	To verify that a specific defect or issue has been fixed in the latest code changes.	To ensure that recent code changes have not adversely affected existing functionality.
Scope	Limited in scope, focusing on the specific defect or issue that was fixed.	Broader in scope, covering various areas of the application to detect regressions.
Test Cases	Reuses the same test cases that initially revealed the defect.	Uses a set of test cases that cover a range of application areas, including previously unaffected parts.
Timing	Performed after the defect is fixed and before the code is released or integrated.	Conducted as a part of the testing process whenever code changes are made, often during regression testing cycles.
Objective	To confirm that the defect is indeed fixed and no longer exists in the updated code.	To verify that existing functionalities remain intact and unaffected by recent code modifications.
Execution Frequency	Typically executed once for each specific defect or issue.	Can be executed multiple times throughout the software development lifecycle, especially during integration and regression testing phases.
Test Data	Uses the same data that initially exposed the defect.	May require a broader range of test data to ensure that various scenarios are covered.
Defect Focus	Focused on a specific defect, usually documented in the defect tracking system.	Concerned with identifying any unintended side effects or regressions across the entire application.

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31.What is Defect Severity and Defect Priority?

Defect priority determines how soon you need to address it. Defect severity reflects the impact of a defect, while defect priority determines its urgency in the development cycle. Defect severity indicates the seriousness of a mistake in the dish – using salt instead of sugar, for example.

Aspect	Defect Severity	Defect Priority
Definition	The seriousness of a defect’s impact on software functionality and performance.	The urgency of fixing a defect based on project and business considerations.
Purpose	Helps in prioritizing defects based on their potential harm and user impact.	Aids in determining the order in which defects should be addressed within the project context.
Categories	Typically includes levels like critical, high, medium, and low, with critical defects being the most severe.	Commonly categorized as immediate, high, normal, and low, with immediate priority given to critical, time-sensitive issues.
Examples	Critical defects may cause system crashes or data loss.	Immediate-priority defects require immediate resolution, often due to impending release deadlines.
Resolution	Higher-severity defects typically receive greater attention and are resolved with urgency.	Higher-priority defects are addressed promptly to align with project schedules and stakeholder needs.

32.What is Accessibility Testing?

Accessibility testing ensures that an application is usable by people with disabilities, conforming to accessibility standards. Accessibility testing ensures everyone can enjoy your dish, regardless of dietary preferences – catering to different dietary needs.

The goal of accessibility testing is to identify and rectify any barriers or obstacles that might prevent people with disabilities from using and interacting with digital content effectively. It promotes inclusive design and compliance with accessibility standards and guidelines.

Here are key aspects of accessibility testing:

Diverse User Base: Accessibility testing considers the needs of users with various disabilities, including visual, auditory, motor, cognitive, and speech impairments. It also caters to different assistive technologies, such as screen readers, voice recognition software, and alternative input devices.

Compliance with Standards: Accessibility testing ensures that digital products adhere to established accessibility standards and guidelines.

Functional and Usability Testing: It covers both functional testing (ensuring all interactive elements work with assistive technologies) and usability testing (evaluating the user experience for people with disabilities).

Testing Scenarios: Accessibility testing involves a range of test scenarios, including keyboard-only navigation, screen reader compatibility, color contrast checks, and testing with alternative input methods.

Benefits: Ensuring accessibility not only enhances the user experience for individuals with disabilities but also aligns with legal requirements in many regions and can expand a product’s user base. Examples of accessibility issues that may be identified during testing include missing alternative text for images, insufficient color contrast, keyboard navigation difficulties, and improper labeling of form fields.

33.What is Build Acceptance Testing?

Build acceptance testing verifies if a build is stable enough for further testing or deployment. 

The primary aim of Build Acceptance Testing is to identify critical defects, issues, or anomalies in the software build promptly. By doing so, it ensures that only stable and reliable builds move forward in the development process, reducing the risk of delivering a flawed product to users.

During this phase, testers meticulously examine the software build, concentrating on fundamental functionalities and core features. They refer to a set of predefined acceptance criteria, which are established in advance to determine whether the build aligns with the project’s quality standards. 

Automation tools may be leveraged to expedite the testing process, particularly for repetitive and critical test scenarios. Automated tests help ensure a thorough assessment of the build’s stability within a short time frame. Any critical defects or issues discovered during Build Acceptance Testing are immediately reported to the development team. This swift feedback loop facilitates timely resolution, preventing the propagation of severe issues to subsequent stages of testing or production environments.

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Build Acceptance Testing also serves as a gatekeeper for the development process. Based on the results of this testing phase, a decision is made on whether the build is acceptable for further testing phases, such as integration testing or user acceptance testing. If significant defects are uncovered, the build may be rejected and sent back to development for fixes. Additionally, a subset of regression test cases may be included in the testing suite to ensure that recent code changes have not inadvertently introduced unexpected regressions.

35.What is Mutation Testing?

Mutation testing is a white-box testing technique where testers modify the application’s source code to assess whether the test suite can detect those changes. It evaluates the effectiveness of test cases. Testers make minute changes in the source code called mutations. The changed source code versions are called mutants. 

Next, testers verify if the existing test cases can identify these changes by applying them to the mutants. 

If not, then test cases are inefficient with serious gaps in functionality. 

If a test case identifies changed code and flags it as failed, then it indicates positive efficacy. Tests are doing exactly what they are meant to do. However, if mutants pass any test cases, then they are inadequate and need reconfiguration to detect all possible errors. 

36.How can you create test cases if requirements are not finalized yet?

Building tests without formal requirements is definitely challenging, but is possible. A few strategies to do that are:

• Run exploratory tests to understand the application, its functions, features and workflows. Use these findings to predict test cases based on customer expectations. 
• Find the use cases most relevant for the app and the industry. Consider user interactions, expected outcomes and edge cases. 
• Use heuristics like happy path, boundary testing, and error guessing to guide test creation. 
• Focus on individual components and features of the application, and create test cases to scan each. 
• Talk to potential users, developers and other stakeholders to get insights into known issues and user preferences. 
• Analyze previous test cases, results and bug reports to find recurring issues and high-risk modules. 

37.Is it possible to test a software program with 100% coverage?

No, it is never possible to completely test a software program completely. This is because:

• Requirements and specifications can be subjective between stakeholders and testers. They may interpret differently and create variant test cases. 
• Testing on the scale required for 100% coverage needs so many inputs, outputs and path combinations that it is not achievable for most teams and organizations. 
• It is not humanly possible to predict every possible user scenario. 

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38.What is a test harness?

When creating functional tests, a test harness is the cluster of software and data needed to test a module or system. It is the environment in which tests are run and results are collected. The elements of a test harness are:

• Test drivers: The programs that call the unit/module being tested. It provides input data and triggers execution. 
• Test stubs: Simplified versions or components on which the unit being tested depends.
• Test data: The input data needed to actually run the test cases, including both valid and invalid data. 
• Test scripts: The scripts or frameworks that automate test execution, manage data, and gather results. 
• Reporting tools: The tools that gather, analyze and report on test results. 
• Debugging tools: The tools used to debug the unit under test. In some cases, this can be the test harness itself. 

39.What is defect cascading?

Defect cascading is a phenomenon in which a single bug in one part of the application leads to a number of other seemingly unrelated bugs emerging in other modules and units. Think of it as a line of dominoes, in which one bug-ridden component triggers issues in all other interconnected modules. 

A simple error, such as a logic issue, bad data handling or flawed algorithms can trigger a cascade of defects. If it isn’t caught in the early stages, it moves through the development lifecycle, interacting with other modules. The issue becomes larger and generates errors in the output of all dependent modules. 

Defect cascading is caused by insufficient testing, strong coupling between modules, sub-par coding, lack of error handling and traceability. 

40.How do you determine the risk level of bugs in functional testing?

When evaluating risk levels of bugs, consider the following categories:

• Critical: The bug triggers a major failure in the system or causes a major data loss. Either way, it leads to serious application instability. 
• High: The bug corrupts data and majorly interferes with system functionality. 
• Medium: The bug reduces usability of some features, but overall, the app remains functional. 
• Low: The bug triggers minor inconveniences; generally cosmetic issues at most.
  

You can also classify the bug based on frequency, likelihood and business impact. 

Frequency:

• Frequent: The bug occurs regularly under certain conditions. 
• Occasional: The bug appears intermittently under specific conditions. 
• Rare: The bug appears rarely and unpredictably.  

Likelihood:

Does the bug appear in most common user scenarios? Does the appearance of the bug repeatedly impact commonly used features or modules? Does the bug disproportionately affect certain user groups?

Business impact:

Does the bug directly contribute to financial losses? Can the bug damage the brand’s reputation and users’ trust? Does the bug violence legal compliance requirements?

41.List all elements of a complete defect report

• Defect ID: Unique identifier to denote the defect. 
• Summary: A brief description of the defect in question. 
• Severity: The impact level of the defect on the software core functionality. 
• Priority: The urgency with which the defect needs to be resolved (depending on its severity).
• Status: The current status of the defect – new, assigned, fixed. 
• Environment Status: Data about the test environment where the bug has been found, including all software and hardware configurations. 
• Assignee: The person to actually fix the bug. 
• Dependencies: Supporting documents, screenshots, logs, test data, and all other dependencies required for the code to work. 
• Date: The date when the bug was first identified. 

Reporter: The individual who actually reported the defect.

Conclusion

As the software industry continues to evolve, functional testing remains a critical aspect of software development. By mastering these top 25 functional testing interview questions, you’ll be well-equipped to demonstrate your expertise in interviews and discussions. Whether you’re just starting your journey in testing or have years of experience, staying updated on the latest concepts and techniques will undoubtedly contribute to your success in the field.

Remember, each question covered here serves as a stepping stone to a deeper understanding of functional testing, making you a more valuable asset to any team or project. 

To further explore automated functional testing solutions and enhance your testing skills, you can visit Testsigma’s resources, such as their blogs on different testing types, automated functional testing, and more. Your journey to becoming a functional testing expert starts here!

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