According to a study by IBM, the cost of identifying and fixing bugs during the testing phase of the software development life cycle is 15 times lower than fixing them post-release. This shows that testing is a critical part of quality assurance (QA).
In this article, we will explore the different types of QA testing, their benefits, and how they can impact your business success.
A Quick List of 13 Types of QA Testing
- Unit testing verifies the functionality of individual units or components of a software application in isolation.
- Integration testing assesses the harmonious functionality of combined software units and components as a single entity.
- System testing determines how the overall system will function in a live environment.
- Manual testing assesses applications using human eyes and intuition.
- Automated testing automates repetitive tasks with scripts.
- AI testing leverages machine learning to enhance and automate testing processes.
- End-to-end Testing provides insights into an application’s behavior from a user’s perspective.
- Functional testing verifies if the software functions as per the requirements.
- Regression testing re-runs previously passed tests after code modifications.
- Visual testing validates the visual aspects of a software application’s user interface.
- Performance testing assesses software applications’s performance and responsiveness under various conditions.
- Compatibility testing ensures the software functions across different platforms and devices.
- Accessibility testing evaluates a website’s usability for people with disabilities
What Are the Different Types of QA Testing?
Quality engineers often employ various test levels and techniques to ensure software quality and functionality. Below, we’ll delve deeper into each QA testing type, categorized into test levels and test techniques.
Test Levels
Test levels refer to the different stages of testing that focus on various aspects and layers of the software application. Here are the primary test levels:
1. Unit testing
Unit testing involves testing the functionality of individual units or components of a software application in isolation to ascertain whether each part functions appropriately on its own. It’s a core functional testing type that’s pivotal for verifying software behavior.
Each testing unit could be a function, method, class, or module. These individual units make up a software application, and if they don’t function properly individually, they won’t work well as a single entity.
It helps to detect bugs quickly in a software component before integrating them into a more sophisticated system.
2. Integration testing
After the individual components involved in a software component have passed the unit testing phase, integration testing is carried out to uncover defects or bugs arising from conflicting codes in integrated modules.
It verifies the functionality of the interface connections between units and ensures the integrated system meets the required standards.
There are two common ways integrated testing can be carried out.
The first is called the Big Bang method, which involves integrating all components and testing them all at once as a single entity.
The second is the incremental method, which involves integrating and testing several units with closely related logic in groups. It could include testing smaller scope components first and then gradually moving to larger components, and vice versa.
3. System testing
System testing is similar to but broader than E2E testing. It encompasses various testing types, including E2E testing, and evaluates the entire system to ensure it meets the overall functional requirements of the application.
It includes transactions and data flows end-to-end testing, data validation and reporting features testing, system functionality testing with actual production-like data, system-level security testing, external interface integration testing, and system performance under load testing.
It’s a critical test that helps quality assurance (QA) testers determine how the overall system will function in a live environment.
Test Techniques
Test techniques are methods employed to carry out testing, each focusing on different aspects and approaches to software testing. Here are the primary test techniques:
4. Manual testing
Manual testing is the traditional software testing method of assessing a software application solely by human testers without using automated testing tools. Quality engineers act as end users, interacting with the system to detect bugs and defects that might affect the overall user experience.
Manual testing is time-consuming, resource-intensive, and generally not scalable. The method often involves creating testing scenarios, carrying out the tests, documenting, and then reporting the outcomes.
Although manual testing gives the QA testers significant control and provides detailed insights, it’s laborious and time-intensive. It also carries a high risk of human error and low test coverage. This explains why many QA testers opted for automated testing to boost their efficiencies.
However, manual testing sometimes comes into the spotlight, especially when creativity and human intuition are necessary. Unless you’re dealing with a very simple system, it’s best to opt for automated or AI testing.
5. Automated testing
Contrary to manual testing, automated testing employs automation testing tools and frameworks to create and run various test cases. The whole test creation and execution process is done with minimal human intervention, saving time, cost, and effort while improving overall testing accuracy and efficiency.
6. AI testing
AI testing involves evaluating the overall performance, reliability, and functionality of a system with artificial intelligence (AI).
AI testing follows the same traditional Software Testing Life Cycle (STLC) as other QA testing types. However, various AI techniques, such as natural language processing (NLP), machine learning (ML), and computer vision, have significantly improved each of its phases.
This helps QA teams perform advanced tasks, such as data analysis, planning, and decision-making, that previously required human intervention.
AI testing is the climax of different types of QA testing, offering speed, efficiency, accuracy, and cost-efficiency in software testing like no other, with little or no human intervention.
You can explore AI testing tools such as QA.tech for maximum productivity in your business.
7. End-to-end testing (E2E)
End-to-end Testing, also called E2E testing, involves testing to verify the performance and functionality of an entire software application’s workflow from start to finish. It’s a subset of system testing.
It involves simulating real-world scenarios and other user interactions to ensure the application functions properly. E2E testing covers all aspects of the application, from user input to backend processing and database interactions, ensuring no stone is left unchecked. It aims to ensure the application meets business requirements and user expectations.
It also provides insight into how the software functions from the end user’s perspective, giving QA testers a comprehensive understanding of the application’s quality before release.
8. Functional testing
Functional testing is used to validate whether the functions of an application’s features meet the specified requirements or standards. It’s also a subset of system testing.
QA testers can perform the test manually or with automated tools, depending on the specific test cases. Quality engineers can use functional testing to verify successful login with valid user credentials, login system behavior for invalid credentials, backend data flow, and product search functionality.
9. Regression testing
Unlike other QA testing types, regression testing is a post-release or post-production test. It’s often conducted after a code update to ensure the update does not introduce a new bug. It’s a subset of system testing.
Sometimes, new code logic may conflict with the existing code, leading to defects and bugs. To rectify this, quality engineers perform regression testing to ensure there are no conflicts in the updated code or correct the code where necessary.
10. Visual testing
Unlike other QA testing types, visual testing focuses on validating the visual aspects such as width, size, position, length, readability, alignment, visibility, and consistency of a software application’s user interface (UI).
It examines the layouts, graphical elements, and overall appearance of the software to ensure it complies with the expected behavior and design across various screen resolutions.
Manual visual testers rely on their eyes to spot bugs and defects.
Quality engineers can also write automation scripts to do the visual testing using the screenshot comparison approach. This involves comparing a reference image with the desired user interface with the actual UI to spot pixel differences between them.
It sometimes mistakes pixel differences arising from dynamic elements, such as time, date, or an eCommerce website cart icon, as visual bugs. However, quality engineers can easily cross this hurdle with AI-augmented visual testing tools.
11. Performance testing
Performance testing assesses the software application’s performance and responsiveness under various conditions to optimize the system’s behavior regarding stability, speed, resource usage, and scalability. It’s a non-functional test.
Performance testing has several subtypes, including load testing, stress testing, endurance testing, scalability testing, spike testing, response time testing, throughput testing, baseline testing, capacity testing, and soak testing.
12. Compatibility testing
Compatibility testing is a QA testing technique that ensures software applications function appropriately across different devices, browsers, environments, and operating systems. It’s also a non-functional test.
Its primary objective is to help quality engineers ensure their applications remain consistent and usable across various configurations. It includes cross-browser testing, cross-device testing, and cross-platform testing.
13. Accessibility testing
Accessibility testing is the process of evaluating the usability of a website, digital content, or software by people with special needs or disabilities. It’s also a non-functional test.
Accessibility testing aims to identify and fix barriers in the software that may hinder such individuals from using the digital product effectively. It checks for compliance with accessibility standards such as the Web Content Accessibility Guidelines (WCAG).
Common accessibility testing validates the availability of a keyboard, screen reader, alt text, multimedia, and color contrast in any digital product.
How Can QA Testing Types Impact Businesses and Improve Workflow?
According to a recent survey, 77 percent (global) and 82 percent (in the United States) of users report abandoning websites due to poor performance and errors. These troubling statistics show software quality can break or improve your company’s reputation in today’s competitive digital landscape.
Evidently, robust software testing is not optional but an absolute must for any successful business. Choosing the appropriate types of software QA testing for your business might be a gentle nudge in the right direction for your business to grow.
Leveraging various QA testing types comes with numerous benefits, including:
1. Improved efficiency
Generally, QA testing will help improve the overall efficiency of your business by spotting bugs and defects while your product is still in the testing phase, just before deploying it to a live environment.
However, leveraging AI QA testing types will help automate repetitive tasks, reduce testing time, and increase your overall efficiency with little or no human intervention. It can generate, execute, and document several test cases simultaneously.
2. Enhanced quality
A thorough QA test ensures high-quality software by reducing the likelihood of post-release bugs and defects. This improves customer satisfaction and retention. and building a brand reputation.
3. Cost savings
According to a report by the Systems Sciences Institute at IBM, it costs six times more to fix a bug or defect found during the implementation phase than to fix one identified during the design phase. It’s more cost-effective and time-saving to fix defects and bugs in the earlier stages of the software development process.
The cost of fixing bugs and defects increases rapidly as the software moves down the development cycle, so identifying and fixing issues earlier in the development cycle through QA testing saves resources and time.
Also, AI-powered testing tools can learn from past test data and adapt to changes in the software, reducing the need for constant script maintenance compared to traditional automation. This doesn’t mean AI-powered QA testing will replace human QA testing; instead, it’ll allow human testers to focus on devising innovative solutions and not the drudgery of mundane and repetitive testing.
How to Leverage Artificial Intelligence in QA Testing
Integrating AI into your QA process doesn’t require a complete overhaul. They include:
- Analyze your current testing process and identify areas for automation.
- Evaluate the available QA testing tools and choose the one that’s compatible with your existing infrastructure.
- Provide the chosen AI tool with high-quality training data, including test cases, bug reports, and user behavior data. The more data there is the better the results.
- Finally, integrate the AI testing tool with your existing development and testing workflows for maximum productivity and efficiency.
Conclusion
QA testing is an essential investment for any software development project. By employing a diverse range of testing methodologies, you can ensure a high-quality product that meets user needs and delivers a positive brand experience.
AI testing provides the most significant advancements in efficiency, bug detection, and the overall workflow improvement of any software development cycle.
As AI technology continues to evolve, its role in QA testing will undoubtedly become even more prominent, shaping the future of software development.
That’s why we recommend leveraging AI-powered tools such as QA.tech to improve your product quality, customer experience, and retention rates while maximizing time and resources.
