Common Functional Testing Interview Questions to Expect in 2023 - IQCode

Concepts of Functional Testing for Software Development

Functional testing is an essential aspect of the software development process. It is a necessary requirement to evaluate the performance of a software system. Although it seems simple, extensive testing is necessary, especially when dealing with complex situations.

Let's explore the deeper concepts of functional testing in this article. Firstly, it's essential to define what functional testing actually means.

What is Functional Testing?

It is the process of testing software components and their functionalities to ensure they work together, and individually as expected. Functional testing is a significant part of the quality assurance process, which is vital to assess if the software system works as intended. During functional testing, the output of each software component is evaluated twice to ensure it meets the required objectives without negatively affecting the rest of the system.

Unlike code-based testing, functional testing is considered a black-box testing technique that does not require source code. It is performed at different development stages and is necessary to verify the component's functionality and validate it against the various functional specifications and requirements.

Moreover, functional testing determines whether a software system and its components are ready to be deployed into a live environment. It prepares the software system or component for production deployment by identifying issues that could arise in production settings.

For freshers, one of the most frequently asked questions during a functional testing interview is -

1. Why is Functional Testing Important?

Types of Functional Testing

Functional testing can be classified into the following types:

1. Unit Testing – tests individual modules or functions of the code

2. Integration Testing – tests how different modules work together

3. System Testing – tests the entire system as a whole

4. Acceptance Testing – tests if the system meets the requirements and specifications

5. Regression Testing – tests if changes or bug fixes did not affect other parts of the system

6. Smoke Testing – tests if the basic functionalities of the system are working

Steps to Perform Functional Testing

Functional testing is carried out to test the functionality of an application based on the business requirements. Here are the general steps to carry out functional testing:

1. IDENTIFY THE REQUIREMENTS: To start with, all the requirements of the application need to be identified and understood thoroughly. This is important to ensure that the application is tested effectively.
2. CREATE TEST SCENARIOS: Based on the identified requirements, test scenarios are created. Test scenarios are a set of steps that need to be followed during the testing process to validate the application.
3. PREPARE TEST DATA: In order to carry out functional testing, test data needs to be prepared. Test data includes input values and expected outputs for each test scenario.
4. EXECUTE TEST SCENARIOS: Once the test scenarios and test data are prepared, functional testing takes place by executing the test scenarios. During this phase, the application is tested based on the test scenarios created.
5. LOG DEFECTS: While executing the test scenarios, if any defects are found, they are logged. Defects are issues or problems found during testing that need to be fixed by the developers.
6. VERIFY DEFECTS: Once the defects are fixed, they need to be verified to ensure that they have been resolved. This is done by executing the test scenario where the defect was found and confirming that the issue no longer exists.
7. REPEAT THE PROCESS: The above steps are repeated until all the test scenarios have been executed and all defects have been resolved.

Functional testing is an important part of the software testing process and ensures that the application meets the business requirements and is functioning as expected.

State the Difference Between Functional and Non-Functional Testing

Functional testing checks if the software or application performs its intended functions or features correctly. It involves testing the various inputs and outputs of the system to verify that it produces correct results.

Non-functional testing, on the other hand, checks the quality of the software or application beyond its functionality. It involves testing aspects such as performance, usability, security, and compatibility to ensure that the system functions optimally. Non-functional testing is focused on testing the system as a whole, rather than individual components.

Functional testing is generally used to verify the functional requirements of the system, while non-functional testing helps to identify issues related to user experience, reliability, and efficiency. Both types of testing are equally important and go hand in hand to ensure that the system meets all the requirements and functions optimally with high-quality standards.

//Example of functional testing

python
def test_login():
  assert login("username", "password") == True
  assert login("wrong_username", "password") == False
  assert login("username", "wrong_password") == False

//Example of non-functional testing

python
def test_performance():
  assert response_time("www.example.com") < 2
  assert server_load("www.example.com") < 80%
  assert user_interface("www.example.com") == "user-friendly"

Explanation of Unit Testing vs Functional Testing

Unit testing and functional testing are two types of software testing used in the software development life cycle.

Unit testing

is a type of testing performed at the unit level of the application, which tests individual units/components of the software. These units are tested in isolation from the rest of the system, to check if the unit works correctly at the code level. It is usually performed by developers and uses frameworks such as Junit and NUnit.

Functional testing

is a type of testing that checks the functionality of the software application as a whole. It tests if the application meets the requirements of the customer or end-user. It is typically performed by QA testers who use black-box testing techniques to execute test cases that simulate real-world scenarios.

To summarize, unit testing focuses on testing specific parts of a codebase in isolation, while functional testing ensures that the entire application meets the functional requirements. Both types of testing are important for delivering high-quality software.

Understanding the Difference between Functional Testing and Regression Testing

Functional testing is a type of testing that ensures that the software or application being tested is working as per the functional requirements. It involves testing each function or feature of the application individually to verify if it meets the required specifications.

Regression testing, on the other hand, is the process of testing old functionalities after making changes to the software or application to make sure that the new changes do not affect the existing functionalities and the system still operates as expected without any issues.

In summary, functional testing ensures that the system is functioning properly as per the requirements, while regression testing checks that the old features still work as intended after making changes or updates to the system. Both types of testing are crucial in software development to minimize the risk of errors and ensure that the system is working optimally.

Explanation of Adhoc Testing

Adhoc testing is a software testing process that is performed without any prior planning or documentation. It is a type of testing that is specifically designed to explore the application in a free-style manner, without following any predefined test cases or scenarios. The purpose of adhoc testing is to uncover defects or issues that may have been missed during structured testing processes.

During adhoc testing, testers randomly test the application by performing different tasks and operations to try and identify any problems. They do not follow any specific test script and instead use their own experience and knowledge to explore the application. Adhoc testing can be done at any stage of the software development life cycle (SDLC) and can be performed by both developers and testers.

Adhoc testing is an important part of testing because it helps to identify and uncover defects that may have gone unnoticed during other types of testing. It also helps to verify that the software is able to perform as expected under different scenarios. However, adhoc testing should not be the only type of testing used, and it should be performed in conjunction with other testing processes, such as structured testing, to ensure complete test coverage.

What is the difference between "build" and "release"?

Building and releasing are two different stages in software development.
Building refers to compiling and linking the source code to create an executable program or library.
Releasing involves creating a final build that is sent to production, and may involve additional steps such as testing, packaging, and documentation.
In short, building is the process of creating software from source code, while releasing is the process of making it available to end users.

Main Differences Between Monkey Testing and Adhoc Testing

Monkey testing is a type of testing performed through random inputs and actions with the aim of discovering software issues, while adhoc testing involves executing test cases that are not predefined and are improvised on the spot.

Monkey testing is completely random and undirected, while adhoc testing is more structured and goal-oriented.

Monkey testing is performed by simulating user behavior by generating random inputs, while adhoc testing is carried out by executing tests in an unplanned manner without any prior preparation.

Monkey testing is usually automated, while adhoc testing is typically manual and is carried out by a human tester.

Overall, while monkey testing is a good way to discover unexpected issues, adhoc testing is more effective in testing specific areas of software and finding potential risks.

State the difference between Alpha and Beta testing

Alpha testing is performed by the in-house testing team before the product is released to external customers. The focus is on the system's functionality, performance, and usability. This test is mostly carried out in a lab environment.

Beta testing, on the other hand, involves releasing the product to external customers who are willing to test the product and provide feedback. The focus of beta testing is to identify bugs, gather user feedback and detect any potential issues that may arise when the product is used in real-world scenarios. This test is carried out in the customer's environment.

Different Test Techniques Used in Functional Testing

Functional testing is a crucial aspect of software testing, and various techniques are used to ensure that the software system functions in accordance with the specified requirements. Some of the different test techniques used in functional testing are as follows:

1. Boundary Value Analysis (BVA) - In this technique, the boundary values of the input domain are tested. The aim is to identify any errors that may arise due to the limits of the input domain.
2. Equivalence Partitioning (EP) - This technique involves dividing the input domain into smaller, non-overlapping partitions. The aim is to reduce the number of tests needed by testing one input from each partition.
3. Decision Table Testing - This technique involves identifying and testing all possible combinations of inputs and their corresponding outputs. It is usually used when there are multiple inputs that can result in different outcomes.
4. State Transition Testing - This technique is used when the system being tested is in a particular state or transition between states. The aim is to test the system thoroughly in each state.
5. Error Guessing - In this technique, the test engineer guesses the errors that may occur in the system and tests the system accordingly. The aim is to identify any errors that may be missed by other techniques.

By using these and other testing techniques, the functionality of a software system can be thoroughly tested, ensuring that it performs in accordance with the specified requirements.

Risk-Based Testing: Factors to Consider and Explanation

Risk-based testing is a software testing approach that prioritizes testing activities based on the level of risk associated with a particular scenario. In this approach, testers identify high-risk areas and allocate resources to test those areas thoroughly.

The following important factors are needed to be considered in risk-based testing:

1. Business Criticality: It is essential to identify how critical the feature or application is to the business. This assessment helps to prioritize the testing activities according to the severity of the risk.

2. User Base: Understanding the user base and the impact of the application on the user is important. In some cases, there may be a high number of users; in others, there may be sensitive data involved.

3. Technical Complexity: A thorough understanding of the technical complexity of the application is necessary. This includes the software architecture, which identifies the components and how they interact with each other, as well as identifying the dependencies between them.

4. Regulatory Requirements: Compliance with regulatory requirements is essential. This includes verifying that necessary security measures and other compliance requirements are adequately tested.

In conclusion, risk-based testing is a critical approach that helps to identify and manage the risks associated with software development projects. By understanding the important factors, a prioritized set of testing activities can be carried out.

Functional Testing Interview Question for Experienced: Equivalence Partitioning

Equivalence partitioning is a testing technique that involves dividing the input data or conditions into different equivalence classes or partitions. It is based on the assumption that if one input value within an equivalence class behaves correctly, then all other input values within the same class will behave correctly as well.

The purpose of using equivalence partitioning is to reduce the number of test cases required to adequately test a system. By dividing the input values into different partitions and testing a representative input value from each partition, we can efficiently test the system's functionality while covering all possible scenarios.

For example, suppose we are testing a login page that requires a username and password. We can divide the input values into three partitions: valid username and password, invalid username, and invalid password. From each partition, we can test a representative input value, such as a valid username and password, an invalid username, and an invalid password. This approach will help us cover all possible scenarios with minimal test cases and ensure that the system works correctly for all input values within each partition.

Understanding Boundary Value Analysis

Boundary Value Analysis is a software testing technique where the testers examine the boundary values of input parameters instead of testing each input value. The input parameters of a program can have minimum, maximum, and nominal values in which boundary values are the minimum and maximum values. By selecting values near the minimum and maximum values, the testers can identify any issues that may arise when the program is executed with those values. This method is most useful in identifying any errors that could occur due to invalid input values.

State the Difference Between Functional and Structural Testing

Functional testing is a type of testing that is carried out to ensure that a software application or system behaves according to its intended functionality. It is essentially concerned with evaluating how the application or system responds to a given set of inputs and whether it produces the expected outputs. This type of testing is typically performed by testers who do not have in-depth knowledge of the internal workings of the application or system.

Structural testing, on the other hand, is a type of testing that is concerned with evaluating the internal logic and structure of a software application or system. It involves testing the code or the architecture of the application to ensure that it is sound and is free from defects. This type of testing is typically performed by developers who have firsthand knowledge of the application code and architecture, and who are responsible for ensuring that it is written correctly.

In summary, functional testing is focused on evaluating the external behavior of the software system, while structural testing is focused on evaluating the internal logic and structure of the software. Both types of testing are important for ensuring the quality of software applications and systems.

What is UFT (Unified Functional Testing)?

UFT stands for Unified Functional Testing. It is a software testing tool that is used to perform automated functional testing of various types of applications. It combines several tools like HP QTP (Quick Test Professional), HP Service Test, and HP UFT Mobile to provide a comprehensive testing solution. UFT works by simulating user actions like keystrokes, mouse clicks, and data entry. It also provides support for a wide range of technologies like Java, .NET, SAP, Oracle, and web-based applications. This allows UFT to be used for testing a variety of applications across platforms and technologies.

Understanding Data-Driven Testing

Data-driven testing is a software testing methodology that involves testing different scenarios with varying input data values to execute the same functionality of an application. It involves using a set of data values stored in an external file such as CSV, Excel, or XML files, as input to test an application's functionality and behavior under different conditions.

This approach helps in testing an application with a large number of data sets quickly and efficiently, saving time and resources. It also helps in uncovering defects and errors that may not have been identified with manual testing, ensuring high-quality software delivery.

With data-driven testing, testers can run automated tests on an application with several data sets, making it possible to catch problems that may occur with different input values. Additionally, this technique enables the testing team to re-use the test case for other similar functionalities, resulting in improved test coverage and faster testing cycle times.

Explanation of Smoke Testing and Sanity Testing

In software testing, Smoke Testing and Sanity Testing are two types of preliminary testing carried out before performing more comprehensive testing.

Smoke Testing is a type of testing that focuses on determining whether the software's most critical functions are working correctly. The purpose of this type of testing is to identify severe issues that might prevent further testing. Smoke Testing is usually carried out after each build to ensure that the application's major components are functioning correctly before commencing further testing.

Sanity Testing is a type of testing that focuses on ensuring that any changes made to the software did not break the software's existing functions. Sanity Testing is performed after major changes have been made to the system before carrying out any comprehensive testing. The primary goal of this type of testing is to determine whether the changes made to the software work as expected, without affecting the application's previous functionality.

In summary, Smoke Testing is carried out to ensure that the application is stable and functional, while Sanity Testing is carried out to validate the changes made to the software.

What is a Requirement Traceability Matrix (RTM)?

A Requirement Traceability Matrix (RTM) is a document that connects requirements throughout the development cycle. It traces and tracks requirements from the project's initiation phase to its closure. The RTM is used to make sure that all necessary requirements are met and to ensure that changes in requirements are properly documented and communicated. This document helps to ensure complete and accurate software development by linking requirements to design, development, testing, and deployment phases.

Code:

N/A

Importance of Requirement Traceability Matrix (RTM)

Requirement Traceability Matrix (RTM) is an essential tool for software development projects. It is used to track every requirement from its origin to the final solution. There are a few reasons why RTM is important:

1. Requirement Coverage: RTM ensures that all of the requirements are covered in the project scope. It makes sure that no requirement is left out or ignored during the development process.

2. Change Management: RTM acts as a reference for change management. It helps in assessing the impact of changes and modifications on the project requirements and progress.

3. Project Quality: RTM enhances project quality by ensuring that all of the requirements are met satisfactorily.

4. Project Maintenance: RTM helps the maintenance team in identifying the origin of the requirement and its related components. This assists in diagnosing and fixing issues in the project.

Overall, RTM is a vital component of software development projects. It helps teams to stay organized, manage changes, and deliver high-quality software solutions.

Difference between Retesting and Regression Testing

Retesting and regression testing are two important software testing techniques:

Retesting: This technique is used when a previously executed test case fails. In such cases, the failed test case is executed again to verify if the same failure occurs. The purpose of retesting is to confirm that the defect has been fixed after it has been reported by testing team.

Regression Testing: This technique is used to ensure that modifications in the code do not have any unintended effects on the previously tested functionality. It is executed after a change in the code or environment and involves running selective test cases to ensure that the changes made have not affected the existing functionality.

In summary, while retesting ensures that a specific defect is fixed, regression testing is context-sensitive and ensures that modifying any code does not impact the functionality of the rest of the system.

Understanding Defect Severity and Defect Priority

Defect severity is the measure of how severe a defect is in terms of its impact on the functionality of the system. It determines the extent to which a defect affects the system under test. High severity defects can severely impact the system's functionality, whereas low severity defects have a minor impact.

Defect priority is the measure of how much importance should be given to fixing a particular defect. It takes into account the severity of the defect and its impact on the system, as well as other factors such as the project schedule and budget. High priority defects are critical and must be fixed immediately, whereas low priority defects can wait until later.

In general, a defect with high priority and high severity should be given the most attention and fixed as soon as possible. However, the priority and severity of a defect may change depending on the project's needs and goals. It is important for developers and testers to prioritize defects and communicate the priorities effectively to ensure that the most critical issues are addressed first.

Understanding Accessibility Testing

Accessibility testing refers to the evaluation of a website or application's ability to be used by people with disabilities, including those with visual, auditory, motor or cognitive impairments. The objective of accessibility testing is to ensure that these users can access and use the product without any difficulties or barriers. This involves checking the product's compliance with accessibility standards such as Web Content Accessibility Guidelines (WCAG) and identifying and remedying any issues that may prevent users with disabilities from effectively using the product.

What is Build Acceptance Testing?

Build Acceptance Testing (BAT) is a software testing process that evaluates whether a build of a software application is acceptable for release. The BAT process involves testing the software application against a set of predefined requirements and specifications to determine if it meets the criteria for acceptance. The goal of BAT is to catch any defects or issues in the software early on in the testing process and before it is released to customers. This helps ensure that the software is of high quality and meets the needs and expectations of users.

Automating Functional Tests: Reasons and Criteria for Choosing the Right Automation Tool

Automating functional tests saves time and effort by executing the tests quickly and efficiently. Plus, it ensures consistent and accurate results. When selecting the right automation tool, there are several factors to consider:

1. Compatibility with the application: Choose a tool that is compatible with your application so that it can interact with all components of the application.

2. Ease of use: The tool should be easy to learn and use. A user-friendly interface helps reduce the learning curve, making it simpler to create and run tests.

3. Object repository: An automation tool should have an object repository that stores all the objects used in the application to reduce redundancy and duplication.

4. Integration with other tools: The automation tool should be integrated with other tools used in the development process. This helps in seamless and faster test execution and reporting.

5. Cost: The cost of the tool must be considered since it can significantly impact the automation budget.

To sum up, automation of functional tests provides several benefits, foremost of which is time and effort-saving. Several criteria must be evaluated to select the most appropriate automation tool for your software application.H3. Functional Test Cases

Functional test cases are a type of testing that focuses on ensuring that the software being tested meets the functional requirements specified by the client or end user. These tests are performed to validate the functionality of the software and ensure that it performs as expected under normal and abnormal conditions.

Functional test cases are usually written from the user's perspective to ensure that the actions users perform are tested. These tests are designed to verify the system as a whole and ensure all inputs and outputs are functioning correctly.

Examples of functional test cases include testing input validation, user authentication, web page rendering and database functionality. Functional testing can be manual or automated and should be performed throughout the software development lifecycle to ensure the final product meets the client's functional requirements.

How to Write Test Cases: Important Points to Consider

Writing effective test cases is crucial for software testing. The following points should be taken into consideration when writing test cases:

- Test case id: Each test case should have a unique identifier to make it traceable and manageable.

- Test case objective: Clearly specify the objective of each test case.

- Test case steps: Write clear, concise and numbered test case steps that can be easily followed by anyone.

- Test data: Provide sufficient test data to ensure that the test covers all possible scenarios.

- Expected result: Define the expected results of each test case.

- Actual result: Document the actual result after executing the test case.

- Status: Mark the status of each test case as "Passed", "Failed" or "Not Run".

- Priority: Assign a priority level to each test case to determine the order in which they need to be executed.

- Complexity: Define how complex each test case is to help in deciding when and how to execute them.

- Traceability: Ensure that each test case has traceability to the requirement, design and code.

By considering these important points when writing test cases, testing teams can ensure that the software they are testing meets all necessary requirements and performs as expected.

Examples of Functional Test Cases

Functional tests verify that an application or system behaves as intended. Here are some examples of functional test cases:

//Example 1: Login Page Functionality Test 1. Verify that the login page loads without any errors. 2. Enter valid login credentials and click on the Login button. 3. Verify that the user is successfully logged in and is directed to the home page. 4. Enter invalid login credentials and click on the Login button. 5. Verify that the error message "Invalid username or password" is displayed.

//Example 2: E-commerce Website Functionality Test 1. Verify that the website loads without any errors. 2. Search for a product and verify that the search results are accurately displayed. 3. Add a product to the cart and verify that the product is added successfully. 4. Remove a product from the cart and verify that the cart is updated. 5. Proceed to checkout and verify that the billing and shipping information is entered correctly. 6. Place the order and verify that the order is placed successfully.

//Example 3: Banking Application Functionality Test 1. Verify that the login page loads without any errors. 2. Enter valid login credentials and click on the Login button. 3. Verify that the user is successfully logged in and is directed to the dashboard page. 4. Transfer money from one account to another and verify that the transfer is successful. 5. Add a new payee and verify that the payee is added successfully. 6. Generate a statement and verify that the statement is accurate.

Possible Login Features to Test in a Web Application

When testing a web application's login feature, the following items should be considered:

- Valid username and valid password
- Valid username and invalid password
- Invalid username and valid password
- Invalid username and invalid password
- Testing case sensitivity in the login fields
- Testing for allowable characters in the fields
- Testing if the user is redirected to the correct page after logging in
- Testing session timeouts and user logouts
- Testing password reset functionality
- Testing simultaneous logins from different devices or browsers
- Testing error messages for clear and appropriate language
- Testing the behavior of the login feature during server downtime or maintenance
- Testing the encryption of the password during transmission and storage

What is the most effective approach to ensure that functional test cases encompass all areas of a product?

One effective approach to ensure that functional test cases cover all areas of a product is to use a combination of techniques such as boundary value analysis, equivalence class partitioning, and decision table testing. Additionally, creating a comprehensive test plan that outlines all the requirements and functionalities of the product can aid in ensuring that all areas are covered. It is also beneficial to involve different team members in the testing process, including developers, testers, and business analysts, in order to get a variety of perspectives and uncover different issues. Regularly reviewing and updating the test plan and test cases can help to ensure that any changes or updates to the product are also tested thoroughly.

Test Cases for Automation

Automated tests are useful in saving time and reducing the risk of human error. However, not all test cases should be automated. Here are some examples of test cases that are good candidates for automation:

1. Tests that are repetitive and time-consuming to execute manually. 2. Tests that need to be executed on multiple configurations or platforms. 3. Tests that require a large amount of data or complex calculations. 4. Tests that need to be executed frequently to monitor the stability of the system. 5. Tests that verify the functionality of critical areas of the application.

It's essential to prioritize which test cases should be automated based on their importance and impact on the system. While it may be tempting to automate all tests, doing so can be time-consuming and inefficient. Instead, focus on the most critical test cases that are likely to uncover the most significant defects.