Common QA Interview Questions and Answers for 2023 - IQCode

Understanding Quality Assurance (QA)

Quality Assurance (QA) is a process used to ensure that software products or services meet the established quality standards. It is a systematic process that verifies whether a product or service fulfills stated requirements. The term "quality" refers to a product or service that is reliable, efficient, and meets user expectations. QA is a proactive process that aims to identify strategies for avoiding bugs in the software development process.

The ISO (International Organization for Standardization) is an essential driver behind QA methods and processes by creating quality standards for companies to follow. QA is often used in conjunction with the ISO 9000 international standard.

For example, Starbucks lost millions of dollars in sales in 2015 because of a problem with their daily system refresh that caused the closure of some point-of-sale registers. This event clearly highlights the importance of having superior quality systems in place.

In the software development lifecycle, QA helps to make the development process more efficient and effective. It is a collaborative process that involves stakeholders, business analysts, developers, and testers. By describing and establishing the requirements for quality standards and the software development process, the QA process helps to increase the productivity of the project team. Additionally, a quality assurance system is designed to boost consumer trust and credibility, while enhancing work procedures and efficiency, allowing companies to be more competitive.

To prepare for interviews relating to QA, candidates can find relevant interview questions for freshers and experienced QA engineers.

QA Interview Questions for Freshers

1. What is the lifecycle of a quality assurance process?

The lifecycle of a quality assurance process typically involves the following stages: planning, design, development, testing, deployment, and maintenance. QA is an ongoing process that seeks to enhance the quality of software products throughout the software development lifecycle.

Difference between Quality Assurance and Testing

Quality Assurance and Testing are two distinct activities that play an important role in software development. Quality assurance is a set of activities that ensure the software meets the desired level of quality and meets the customer's requirements. Testing, on the other hand, is a process of identifying defects or errors in the software.

The main difference between Quality Assurance and Testing is that Quality Assurance is a preventive measure to ensure the quality of the software before it is released, while Testing is a corrective measure to identify and fix defects in the software after it has been developed.

Quality Assurance involves creating standards, processes, and procedures that ensure the software meets the required quality level. It includes activities such as reviews, audits, and inspections. Quality Assurance also involves training and educating the development team to ensure they follow the established processes and procedures.

Testing, on the other hand, involves executing the software with the intent of finding defects or errors. It includes activities such as functional testing, performance testing, and security testing. Testing is critical to detect defects that may impact the software's functionality, usability, performance, and security.

While Quality Assurance and Testing are different activities, they are both essential to ensure the quality of the software. Without Quality Assurance, defects and errors are likely to occur throughout the development process, making it difficult and expensive to fix them. Without Testing, defects may go undetected, resulting in poor quality software that does not meet the customer's requirements.

//Example code for testing

Difference between Test Plan and Test Strategy

Test plan and test strategy are both important documents in the software testing process, but they serve different purposes. The following are the main differences:

Test Plan:

• A test plan describes the scope, approach, resources, and schedule of testing activities.
• It outlines the objectives, strategies, and methods that will be used to ensure software quality.
• The test plan identifies test items, features to be tested, testing tasks, and any associated risks.
• It ensures that all testing requirements are met and provides a road map for testing.

Test Strategy:

• A test strategy outlines the testing approach and guidelines to be followed for achieving the testing objectives.
• It is a high-level document that defines the overall testing approach and identifies the testing types, tools, and resources to be used.
• The test strategy describes how to standardize the testing process and ensure that it is consistent across the project.
• It helps in identifying the risks, enabling risk mitigation planning, and communicating it to the stakeholders.

Test plan and test strategy documents are interrelated and complementary. The test strategy provides the guidelines for creating a comprehensive test plan which outlines the testing methods, approach, and tools used in achieving the testing objectives.

Understanding Build and Release in the Context of Quality Assurance

In Quality Assurance, build and release are two different processes that are often used interchangeably, but they have distinct differences.

Build refers to the process of assembling the software code into its final executable state. It involves compiling the source code, integrating the code with relevant libraries, and making sure that all the code and supporting files are packaged correctly. The build process creates a software artifact that can be installed on a user's system.

Release, on the other hand, refers to the process of making the software available to end-users. This process includes testing, deployment, and distribution of the software. Release management deals with coordinating the activities required to ensure that the new software is in line with the user's expectations, meets the set quality standards, and solves the intended end-user problems.

In summary, build is about creating the software executable, while release is about making the software available to the end-user. They are related, but different processes in the Quality Assurance cycle.

Understanding Bug Leakage and Bug Release

Bug Leakage refers to a situation where a bug is present in the software build, but it goes unnoticed during the testing phase and gets released to the production environment. This can result in a significant impact on the system, leading to issues such as system failures or errors.

On the other hand, Bug Release is when a build is released to the testing team, and it contains a known bug. The development team decides to release the build, regardless of the known issue.

Both Bug Leakage and Bug Release can have negative impacts on the software development process. Therefore, it is essential to have a robust testing process in place to catch and eliminate bugs before the release of the software.

Understanding Traceability Matrix (TM) in Quality Assurance

In the field of quality assurance, a traceability matrix (TM) is a document that helps in tracing and managing the requirements of a software project. It establishes a connection between the customer's requirements, testing efforts, and the final product.

The TM provides a clear overview of the status of the project requirements and ensures that all requirements are met in the final product. It also helps in identifying the relationship between the requirements, test cases, and defects.

Overall, the TM is a useful tool for project managers and quality assurance teams to ensure that the final product meets the customer's expectations and requirements. It helps to maintain transparency and accountability throughout the project, leading to an efficient and successful outcome.

Understanding Defect Leakage Ratio in the Context of Quality Assurance

Defect leakage ratio is a crucial metric in quality assurance that refers to the number of defects missed during the testing phase and subsequently found by customers or end-users after the product or software has been released. It is a measure of the effectiveness of the quality assurance process, and a high defect leakage ratio indicates that there may be gaps in the testing process.

The defect leakage ratio is calculated as the number of defects found by customers or end-users after the release of the product divided by the total number of defects. This ratio can be reduced by improving the quality assurance process, including testing techniques, defect tracking, and collaboration between development and testing teams.

By keeping the defect leakage ratio at a minimum, quality assurance teams can ensure that the product or software meets the desired standards of quality, functionality, and usability before being released to the end-users.

Difference between Quality Assurance (QA) and Quality Control (QC)

Quality Assurance (QA) and Quality Control (QC) are two important concepts in the field of software testing. While both QA and QC are related to ensuring the quality of a product, they differ in their approach and scope.

QA refers to the systematic process of ensuring that a product is meeting the required quality standards throughout the entire software development lifecycle. This involves defining and implementing policies, processes, and procedures to achieve quality goals, and continuously monitoring and improving the overall process.

On the other hand, QC is a reactive process that involves detecting and correcting defects in the product before it is released to the market. It involves executing various types of tests, such as functional, performance, and security tests, to ensure that the product is meeting the quality standards.

In summary, QA is a proactive approach to ensure that quality is built into the product right from the beginning, whereas QC is a reactive approach to detect and fix defects in the product after it has been developed.

// Sample code illustrating the difference between QA and QC

function calculateSum(num1, num2) {

   // Quality Assurance (QA)

   if(isNaN(num1) || isNaN(num2)) {

       throw new Error('Invalid input: inputs should be numbers');

   }

   const sum = num1 + num2;

   // Quality Control (QC)

   if(sum !== (num1 + num2)) {

       throw new Error('Error in calculation: sum does not match expected result');

   }

   return sum;

}

In the above code, the QA process is implemented by checking if the inputs to the calculateSum function are numbers, and throwing an error if they are not. This ensures that the function is used correctly, and the inputs are valid. On the other hand, the QC process is implemented by checking if the calculated sum matches the expected result, and throwing an error if it does not. This ensures that the function is working as expected, and any defects are detected and fixed before the product is released.

Monkey Testing in Quality Assurance

Monkey testing is a technique used in Quality Assurance to check the behavior of an application under unpredictable conditions. In this type of testing, the tester randomly clicks on the buttons or links of the application without following any specific test case. The purpose of this testing is to identify any unexpected behavior of the application that can be caused by the user's actions. The monkey testing helps the QA team to ensure that the application is stable and can handle any unpredicted event that may occur during its usage.

Understanding Gorilla Testing in Quality Assurance

Gorilla Testing is a type of testing performed by an experienced and skilled tester who conducts random and chaotic testing on software applications in order to identify any defects or bugs that may have been overlooked during regular testing. This testing is usually performed without a specific test plan or script and can include checking the application's response to unexpected inputs or actions. The aim of gorilla testing is to improve the quality of the application by detecting any potential errors that may have otherwise gone unnoticed.

Difference Between Gorilla Testing and Monkey Testing

Gorilla Testing and Monkey Testing are two types of testing techniques that fall under the category of non-functional testing. They are both used to find defects or issues that can occur in the software under test. However, there are some differences between these two testing techniques:

• Gorilla Testing: This testing technique involves testing a specific module or functionality of the software under test in depth. The aim is to find as many defects as possible in that module or functionality. The testing is performed by an experienced tester who knows the product well. The primary goal of gorilla testing is to check the robustness of the system by focusing on critical areas of the application.
• Monkey Testing: This testing technique is a random testing approach where the tester randomly navigates through the application by clicking on different areas of the application randomly. The goal of monkey testing is to identify defects that may not be found by other types of testing. This technique is particularly useful when time is limited, and it is not possible to cover all scenarios through other testing techniques.

In summary, gorilla testing is a focused testing approach in which an experienced tester tests a specific functionality or module of the software, while monkey testing is a random testing approach where the tester randomly navigates through the application to identify defects.

// Example of Gorilla Testing
public class ShoppingCart {
  // Methods for adding/removing items from cart
  // Methods for calculating total cost and taxes
}

// Example of Monkey Testing
public void testRandomClicks() {
  // Randomly click on different areas of the application
  // Record any issues or defects found
}

Testware in Quality Assurance

In quality assurance, Testware refers to the collection of software, data, procedures, and documentation that are used in the testing of a software system or application. Testware is created by the testers and includes the test cases, test scripts, and test data that are used to validate and verify that the software system or application meets the specified requirements. Testware helps to ensure that the software is of high quality and free from defects before it is released to the end-users. It is a critical component of the overall software development life cycle and plays a significant role in the success of software projects.

Understanding Data-Driven Testing

Data-driven testing is a test automation technique where test cases are parameterized using test data from external sources such as spreadsheets or databases. This allows for the creation of a single test case that can be executed multiple times with different data sets. The objective of data-driven testing is to increase test coverage and efficiency by reducing the need for manual test case creation and execution, and to identify defects that may not be found through traditional testing methods.

Ways to Ensure Thorough and Comprehensive Testing

To ensure that testing is thorough and comprehensive, the following strategies can be implemented:

• Develop a clear understanding of the project’s requirements and determine the scope of testing.
• Create comprehensive test cases that span all possible input scenarios.
• Use automated testing tools to increase test coverage and reduce human errors.
• Perform integration testing to ensure that all modules are working in conjunction with each other.
• Perform performance and load testing to ensure that the system can handle high traffic and usage volumes.
• Perform regression testing to ensure that new updates or features do not negatively impact existing functionality.
• Collaborate with development and other teams to identify potential issues before testing begins and to prioritize testing efforts accordingly.
• Continuously monitor and track testing results and modify testing strategies as necessary.

By following these strategies, one can ensure that testing is thorough and comprehensive, reducing the likelihood of defects and errors in the final product.

//example of automated testing with Cypress

describe('Login functionality', () => {
  it('Logs in user with correct credentials', () => {
    cy.visit('/login')
    cy.get('input[name="email"]').type('[email protected]')
    cy.get('input[name="password"]').type('password123')
    cy.get('button[type="submit"]').click()
    cy.url().should('include', '/dashboard')
  })
  
  it('Displays error message with incorrect credentials', () => {
    cy.visit('/login')
    cy.get('input[name="email"]').type('[email protected]')
    cy.get('input[name="password"]').type('wrongpassword')
    cy.get('button[type="submit"]').click()
    cy.contains('Invalid email or password.')
  })
})

In the above example, we use the Cypress framework to automate the testing of a login functionality. This ensures that the login process is tested thoroughly and comprehensively, with all possible input scenarios covered.

Various Artifacts Referred When Writing Test Cases

When writing test cases, there are several artifacts that can be referred to, such as:

1. Requirements documentation 2. Functional specifications 3. Design documents 4. Use cases 5. Business rules 6. Acceptance criteria 7. User stories 8. Prior bug reports 9. Defect prevention or quality improvement plans 10. Industry standards and regulations.

Referring to these artifacts helps ensure that the test cases cover all the necessary scenarios and requirements, reducing the chances of defects and enhancing the overall quality of the product.

Understanding Test Cases and Best Practices for Writing Them

Test case refers to a set of steps, conditions and inputs that are executed to validate if a particular system, application or feature is working as expected. In simple terms, test cases are designed to identify any errors, defects or gaps in functionality in software or system.

Some good practices for writing effective test cases include:

• Make sure the test case is clear, concise, and easy to understand even for someone unfamiliar with the code base.
• Use descriptive and informative names for both the test case and any variables used.
• Cover all possible scenarios including positive, negative and edge cases to ensure comprehensive testing.
• Ensure each test case is independent of other test cases and can be executed and debugged separately.
• Use appropriate tools and automated test case writing techniques to ensure fast, efficient and reliable testing.
• Be mindful of time, budget, and resources constraints when designing test cases.
• Perform regular review and refinement of test cases to account for changes in code or requirements and to ensure optimal coverage of all features and functionalities.

Overall, having well-defined test cases can help ensure that software and systems are robust, reliable, and perform as expected under a variety of real-world conditions.

Experienced QA Interview Question: Regression Testing

Regression testing is a type of software testing that involves retesting previously tested software features after introducing new changes or updates to ensure that the existing functionality of the software has not been affected.

In regression testing, we should select the test cases that cover the areas of the software that have been changed or updated. These test cases are also selected based on their priority and their impact on the software's overall functionality. The objective of regression testing is to ensure that the software still works as intended and that new changes or updates have not introduced any bugs or issues.

Understanding Risk in Quality Assurance

Risk in the context of quality assurance refers to the possibility of an event or circumstance occurring that could negatively impact the quality of the product or service being provided. This can include anything from defects in the product to delays in delivery or even security breaches.

The five dimensions of risk that must be considered in quality assurance are:

1. Probability - The likelihood of a risk occurring. 2. Impact - The severity of the consequences if the risk does occur. 3. Control - The ability to mitigate or manage the risk. 4. Time - The window of opportunity for the risk to occur. 5. Scope - The extent of the impact if the risk does occur.

By considering these dimensions, quality assurance professionals can identify potential risks, assess their likelihood and severity, and determine the appropriate course of action to mitigate or manage them. This helps to ensure that the product or service being provided meets the required standards of quality and reduces the likelihood of negative outcomes.

Understanding Severity and Priority of Defects in Quality Assurance

In Quality Assurance, severity and priority are important concepts when dealing with defects. Severity refers to the impact of a defect on the system or application. It is usually categorized into four levels - low, medium, high, and critical. A critical severity defect affects the system completely and renders it unusable, while a low severity defect does not have a significant impact on the system's performance.

On the other hand, priority refers to the order in which defects must be resolved. It is typically classified into four levels - low, medium, high, and urgent. An urgent priority defect must be resolved immediately as it can critically impact the system or business operations. In contrast, a low priority defect can be deferred as it does not significantly affect the system.

To summarize, the difference between severity and priority is that severity defines the impact of the defect, while priority defines the order in which it must be fixed. Both these concepts are essential in ensuring the quality of a system or application.

Quality Audit in the Context of Quality Assurance

A Quality Audit is a process that evaluates whether a product or service meets the established set of quality standards and requirements. In the context of Quality Assurance, a Quality Audit is conducted to ensure that the processes and methodologies used to develop and test the product or service are in compliance with the defined quality standards. The objective of the audit is to identify areas for improvement and implement corrective actions to improve the overall quality of the product or service. It helps in building trust and confidence among stakeholders that the product or service will meet their expectations and requirements.

Determining the Required Amount of Testing for a Software in Quality Assurance

In order to determine the appropriate amount of testing for a piece of software in the context of quality assurance, there are several factors that need to be considered. These include the complexity of the software, its intended use and functionality, the level of risk associated with its use, and any regulatory or compliance requirements that must be met.

It is important to establish a clear testing plan and strategy, which should include identifying the types of testing that will be performed (such as functional testing, performance testing, and security testing), the specific test cases that will be used, and the expected outcomes of each test.

To ensure that testing is comprehensive and effective, it is important to involve all stakeholders in the development process, including developers, testers, and users. Testing should also be conducted throughout the development lifecycle, with each new build or release being thoroughly tested before it is deployed.

By taking a methodical and comprehensive approach to testing, it is possible to ensure that software is of the highest possible quality and meets all required standards and regulations.

Difference between Load Testing and Stress Testing

Load testing and stress testing are both performance testing techniques but they have different objectives and outcomes.

Load testing is used to evaluate the system's behavior under normal and expected conditions. The aim is to identify how the system behaves when a certain amount of load is applied and whether it can handle the expected number of concurrent users without compromising its performance. Load testing involves simulating realistic scenarios to measure the system's response time, throughput, and resource utilization.

Stress testing, on the other hand, is used to evaluate the system's behavior when it is subjected to extreme conditions beyond its normal capacity. The aim is to identify the system's breaking point and determine the maximum load it can handle before it fails. Stress testing involves simulating scenarios that push the system beyond its limits to measure its stability, recovery, and error handling capabilities.

Therefore, the main difference between load testing and stress testing lies in their objectives. While load testing aims to evaluate and optimize the system's performance under normal conditions, stress testing aims to evaluate and prepare the system for unexpected and extreme conditions.

//Example code snippet for load testing using JMeter

//Example code snippet for stress testing using Gatling

Differentiating between Functional and Non-Functional Testing

Functional testing is a type of testing that checks if the system meets the required specification and performs its intended functions correctly. It ensures that the software is tested from an end-user perspective, making sure that all features are working as expected. Test cases are based on the system requirements and are executed to discover, identify, and report any issues.

Non-functional testing, on the other hand, ensures that the system meets the non-functional requirements, such as performance, usability, security, and scalability. It tests that the software meets the quality standards and requirements of different stakeholders. Non-functional testing checks how well the system performs under different conditions, such as heavy traffic, different network environments, and high usage volumes.

In summary, functional testing focuses on the functional requirements of the system, while non-functional testing focuses on the non-functional requirements of the system.

// Example of functional testing
function testLogin() {
  // Test user login and validate that the user is redirected to the correct page
  // Verify that the user's credentials are correct and they can log in successfully
}

// Example of non-functional testing
function testPerformance() {
  // Analyze system performance under different loads and identify any bottlenecks
  // Verify that the system can handle heavy traffic and high usage volumes without crashing or slowing down
}

Understanding Black Box and White Box Testing and their Differences

In software testing, Black Box and White Box testing are two different approaches to test a software application. Let's understand each of them and differentiate between them.

Black Box Testing: It is also known as functional testing, where the tester tests the software application without looking at the code. Here, the tester checks the functionality of the software application according to the requirement specification. Black Box Testing is performed to examine whether the application fulfills the end-user requirements or not. The tester does not require the knowledge of the internal system architecture or code. The examples of Black Box Testing are system testing, acceptance testing, and integration testing.

White Box Testing: It is also known as structural testing, where the tester tests the internal structure of the application. In this approach, the tester has the complete knowledge of the code and the internal structure of the application. White Box Testing helps to identify the design flaws, logical errors or any other defects that impact the functionality of the application. This testing is done on code level and it requires knowledge of programming. The examples of White Box Testing are unit testing, integration testing and code coverage testing.

Differences Between Black Box and White Box Testing: Black Box Testing is done from the user's point of view, while White Box Testing is done from the developer's point of view. Black Box Testing does not require any knowledge of the internal structure of the application, whereas in White Box Testing the tester needs to have knowledge of the internal structure and code of the application. Black Box Testing focuses on the functional behavior of the application, while White Box Testing focuses on the code structure, design and implementation of the application. Black Box Testing is performed in the later stages of software development, and White Box Testing is performed early in the software development lifecycle. The objective of Black Box Testing is to test the functional requirements of the application, whereas the objective of White Box Testing is to identify the defects in the code and improve the code quality.

Understanding Bug/Defect Triage in the Context of Quality Assurance

Bug/defect triage is the process of determining the priority of bugs/defects identified during the testing phase of software development. It involves analyzing and categorizing bugs based on their severity, impact on the system, and likelihood of occurrence. The goal of bug triage is to prioritize the bugs that need immediate attention and address them first. This process helps to ensure that the development team is focused on the most critical issues and allows for efficient use of time and resources. Quality Assurance plays an important role in the bug/defect triage process by working with the development team to identify and prioritize the bugs/defects. By prioritizing the bugs and defects, Quality Assurance helps to ensure that the development team can quickly resolve the most critical issues and deliver high-quality software to the end-users.

Understanding Stubs and Drivers and their Differences

In software development, stubs and drivers are both types of software components used in testing. Stubs are used to simulate the behavior of a module that a software component being tested depends on, while drivers are used to facilitate the testing of a module that depends on another module.

The main difference between the two is that stubs are used in a top-down approach to software development, where modules are developed from the top-level down to the lower levels, while drivers are used in a bottom-up approach, where modules are developed from the lower levels up to the top level.

Stubs are used to test modules that are higher up in the hierarchy, while the lower-level modules are still being developed. Once the lower-level modules are developed, the stubs are replaced with the actual modules. On the other hand, drivers are used to test modules that are lower in the hierarchy, while the higher-level modules are still being developed. Once the higher-level modules are developed and integrated, the drivers are no longer needed.

Overall, stubs and drivers help developers test their code in a modular fashion, allowing for efficient and effective software development and testing.